Table of contents
  1. Story
    1. Narrative
    2. Slides
      1. Slide 1 Data Science for USGS Minerals Big Data
      2. Slide 2 Evolution at the USGS
      3. Slide 3 USGS Mineral Resources Program (MRP)
      4. Slide 4 USGS Commodity Statistics and Information
      5. Slide 5 Adobe Acrobat Convert From PDF Tool
      6. Slide 6 Adobe Acrobat Convert From PDF to Excel
      7. Slide 7 Mineral Resources On-Line Spatial Data: National Geochemical Survey Database
      8. Slide 8 Mineral Resources On-Line Spatial Data: Mineral Resources Data System (MRDS)
      9. Slide 9 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Index
      10. Slide 10 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Attachments
      11. Slide 11 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Find
      12. Slide 12 Data Science for USGS Minerals Big Data: Excel Knowledge Base Find
      13. Slide 13 Data Science for USGS Minerals Big Data: Spotfire Cover Page
      14. Slide 14 Data Science for USGS Minerals Big Data: Minerals Commodity Summaries 2015 Tables in Spotfire
      15. Slide 15 Data Science for USGS Minerals Big Data: MRDS-shp in Spotfire
      16. Slide 16 Some Conclusions and Recommendations
  2. Spotfire Dashboard
  3. Research Notes
    1. MRP Science & Information Forum
      1. Program Schedule
        1. Tuesday, May 5
        2. Wednesday, May 6
        3. Thursday, May 7
      2. Poster Presentations
    2. Resources
    3. Email
  4. Slides
    1. Slide 1 Making the Story Behind USGS EM-EH Data Come Alive
    2. Slide 2 Chinese Proverb
    3. Slide 3 Tables with Spatial & Temporal Data
    4. Slide 4 Dense Static Maps
    5. Slide 5 USGS Energy, Minerals, and Environmental Health Projects
    6. Slide 6 Energy Resources Program (ERP)
    7. Slide 7 Mineral Resources Program (MRP)
    8. Slide 8 Environmental Health Program (EHP)
    9. Slide 9 Science and Decisions Center (SDC)
    10. Slide 10 The Rise of Public Engagement
    11. Slide 11 Outline of Visualization Approaches
    12. Slide 12 What Makes a Good Infographic?
    13. Slide 13 Infographic
    14. Slide 14 Minerals Use in Safety Applications in the Workplace
    15. Slide 15 Mineral Resources
    16. Slide 16 Mobile App
    17. Slide 17 Minerals Infographic
    18. Slide 18 Mineral Tweets
    19. Slide 19 Elements of a Smartphone
    20. Slide 20 USGS Table in PDF
    21. Slide 21 The Toxic Twenty Infographic
    22. Slide 22 Geo-Time Travel with Time-Lapse
    23. Slide 23 Wind Map
    24. Slide 24 Mineral Commodity Summaries
    25. Slide 25 Spatiotemporal Data in a Bar Graph
    26. Slide 26 Gapminder Visualization
    27. Slide 27 Wind Farm Map
    28. Slide 28 Department of Energy MapBox
    29. Slide 29 Minerals Data Table in PDF
    30. Slide 30 D3 and Cesium Demo
    31. Slide 31 Google Maps Earth
    32. Slide 32 Produced Waters Map Viewer Application
    33. Slide 33 The National Broadband Map
    34. Slide 34 Example of a Table with Geospatial Data
    35. Slide 35 Example of a Simple Interactive Map
    36. Slide 36 Map with Special Symbology
    37. Slide 37 Example of a Map Generated Using MapBox
    38. Slide 38 Geospatial Storytelling
    39. Slide 39 Copper
    40. Slide 40 Big Holes
    41. Slide 41 Static Map for Large Poster
    42. Slide 42 Esri Story Map 1
    43. Slide 43 Table of Hydraulic Fracturing
    44. Slide 44 Esri Story Map 2
    45. Slide 45 Exploring Interactive Visualization
    46. Slide 46 Large Matrix Table
    47. Slide 47 Esri Story Map 3
    48. Slide 48 Mineral Map Needing Color
    49. Slide 49 Table of Mineral Commodities
    50. Slide 50 Combining Map andTable
    51. Slide 51 Table Referencing Spatial Regions
    52. Slide 52 Pollution Burdens
    53. Slide 53 Example of Stacked Line Graphs
    54. Slide 54 Interactive Line Graph Interface
    55. Slide 55 Use the D3 Javascript Library to Create Interactive Graphs
    56. Slide 56 Mineral Resources On-Line Spatial Data 1
    57. Slide 57 Mineral Resources On-Line Spatial Data 2
    58. Slide 58 World Energy Survey Analysis TIBCO Spotfire
    59. Slide 59 Mobile and Web Apps
    60. Slide 60 Mineral Resource Online Data Catalog 1
    61. Slide 61 Pttrns
    62. Slide 62 NASA Earth-Now
    63. Slide 63 Challenge.gov toxicSlayar
    64. Slide 64 Mineral Resource Online Data Catalog 2
    65. Slide 65 USGS Toxic Substances Website
    66. Slide 66 Climate Change Impacts in the United States PDF Report
    67. Slide 67 Climate Change Impacts in the United States Website
    68. Slide 68 Pathway Towards Engaging Crowds
    69. Slide 69 What is Worth Highlighting
    70. Slide 70 EMEH Data Formats
    71. Slide 71 The Value of a Good API
    72. Slide 72 EM-EH Challenges & Hackathons
    73. Slide 73 Crowdsourcing / Geo-Hacking
    74. Slide 74 Civic Hacking Goals
    75. Slide 75 Potential Visualization Tools
    76. Slide 76 What I Need From You
    77. Slide 77 Positives of Civic Hacking
    78. Slide 78 Questions?
  5. USGS Releases Data Management Instructional Memos
    1. Scientific Data Management Foundation
    2. Metadata for Scientific Data, Software, and Other Information Products
    3. Review and Approval of Scientific Data for Release 
    4. Preservation Requirements for Digital Scientific Data 
  6. Mineral Commodity Summaries 2015
    1. Cover Page
    2. Inside Cover Page
    3. Other Information
      1. INSTANT INFORMATION
      2. KEY PUBLICATIONS
      3. WHERE TO OBTAIN PUBLICATIONS
    4. General
      1. Introduction
      2. Growth Rates of Leading and Coincident Indexes for Mineral Products
      3. The Role of Nonfuel Minerals in the U.S. Economy
      4. 2014 U.S. Net Import Reliance for Selected Nonfuel Mineral Materials
      5. Significant Events, Trends, and Issues
        1. Figure 1 Major Metal-Producing Areas
        2. Figure 2 Major Industrial Mineral-Producing Areas Part I
        3. Table 1 U.S. Mineral Industry Trends
        4. Table 2 U.S. Mineral-Related Economic Trends
        5. Figure 3 Major Industrial Mineral-Producing Areas Part II
        6. Table 3 Value of Nonfuel Mineral Production in the United States and Principal Nonfuel Minerals Produced in 2014 p, 1
      6. Appendix A—Abbreviations and Units of Measure
      7. Appendix B—Definitions of Selected Terms Used in This Report
        1. Terms Used for Materials in the National Defense Stockpile and Helium Stockpile
        2. Depletion Allowance
      8. Appendix C—Reserves and Resources
        1. Part A—Resource/Reserve Classification for Minerals1
          1. Introduction
          2. Resource-Preserving Definitions
          3. Figure 1 Major Elements of Mineral-Resource Classification, Excluding Reserve Base and Inferred Reserve Base
          4. Figure 2 Reserve Base and Inferred Reserve Base Classification Categories
        2. Part B—Sources of Reserve Data
      9. Appendix D—Country Specialists Directory
        1. Africa and the Middle East
        2. Asia and the Pacific
        3. Europe and Central Eurasia
        4. North America, Central America, and the Caribbean
        5. South America
        6. Country specialist, Telephone, & E-mail
    5. Mineral Commodities
      1. Abrasives (Manufactured)
        1. Table Salient Statistics—United States
        2. Table Tariff Item
        3. Table World Capacity Production
      2. Aluminum
      3. Antimony
      4. Arsenic
      5. Asbestos
      6. Barite
      7. Bauxite and Alumina
      8. Beryllium
      9. Bismuth
      10. Boron
      11. Bromine
      12. Cadmium
      13. Cement
      14. Cesium
      15. Chromium
      16. Clays
      17. Cobalt
      18. Copper
      19. Diamond (Industrial)
      20. Diatomite
      21. Feldspar
      22. Fluorspar
      23. Gallium
      24. Garnet (Industrial)
      25. Gemstones
      26. Germanium
      27. Gold
      28. Graphite (Natural)
      29. Gypsum
      30. Helium
      31. Indium
      32. Iodine
      33. Iron and Steel
      34. Iron and Steel Scrap
      35. Iron and Steel Slag
      36. Iron Ore
      37. Iron Oxide Pigments
      38. Kyanite and Related Minerals
      39. Lead
      40. Lime
      41. Lithium
      42. Magnesium Compounds
      43. Magnesium Metal
      44. Manganese
      45. Mercury
      46. Mica (Natural)
      47. Molybdenum
      48. Nickel
      49. Niobium (Columbium)
      50. Nitrogen (Fixed)—Ammonia
      51. Peat
      52. Perlite
      53. Phosphate Rock
      54. Platinum-Group Metals
      55. Potash
      56. Pumice and Pumicite
      57. Quartz Crystal (Industrial)
      58. Rare Earths
      59. Rhenium
      60. Rubidium
      61. Salt
      62. Sand and Gravel (Construction)
      63. Sand and Gravel (Industrial)
      64. Scandium
      65. Selenium
      66. Silicon
      67. Silver
      68. Soda Ash
      69. Stone (Crushed)
      70. Stone (Dimension)
      71. Strontium
      72. Sulfur
      73. Talc and Pyrophyllite
      74. Tantalum
      75. Tellurium
      76. Thallium
      77. Thorium
      78. Tin
      79. Titanium and Titanium Dioxide
      80. Titanium Mineral Concentrates
      81. Tungsten
      82. Vanadium
      83. Vermiculite
      84. Wollastonite
      85. Yttrium
      86. Zeolites (Natural)
      87. Zinc
      88. Zirconium and Hafnium
  7. National Geochemical Survey Database
  8. Mineral Resources Data System (MRDS)
  9. NEXT

Data Science for USGS Minerals Big Data

Last modified
Table of contents
  1. Story
    1. Narrative
    2. Slides
      1. Slide 1 Data Science for USGS Minerals Big Data
      2. Slide 2 Evolution at the USGS
      3. Slide 3 USGS Mineral Resources Program (MRP)
      4. Slide 4 USGS Commodity Statistics and Information
      5. Slide 5 Adobe Acrobat Convert From PDF Tool
      6. Slide 6 Adobe Acrobat Convert From PDF to Excel
      7. Slide 7 Mineral Resources On-Line Spatial Data: National Geochemical Survey Database
      8. Slide 8 Mineral Resources On-Line Spatial Data: Mineral Resources Data System (MRDS)
      9. Slide 9 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Index
      10. Slide 10 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Attachments
      11. Slide 11 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Find
      12. Slide 12 Data Science for USGS Minerals Big Data: Excel Knowledge Base Find
      13. Slide 13 Data Science for USGS Minerals Big Data: Spotfire Cover Page
      14. Slide 14 Data Science for USGS Minerals Big Data: Minerals Commodity Summaries 2015 Tables in Spotfire
      15. Slide 15 Data Science for USGS Minerals Big Data: MRDS-shp in Spotfire
      16. Slide 16 Some Conclusions and Recommendations
  2. Spotfire Dashboard
  3. Research Notes
    1. MRP Science & Information Forum
      1. Program Schedule
        1. Tuesday, May 5
        2. Wednesday, May 6
        3. Thursday, May 7
      2. Poster Presentations
    2. Resources
    3. Email
  4. Slides
    1. Slide 1 Making the Story Behind USGS EM-EH Data Come Alive
    2. Slide 2 Chinese Proverb
    3. Slide 3 Tables with Spatial & Temporal Data
    4. Slide 4 Dense Static Maps
    5. Slide 5 USGS Energy, Minerals, and Environmental Health Projects
    6. Slide 6 Energy Resources Program (ERP)
    7. Slide 7 Mineral Resources Program (MRP)
    8. Slide 8 Environmental Health Program (EHP)
    9. Slide 9 Science and Decisions Center (SDC)
    10. Slide 10 The Rise of Public Engagement
    11. Slide 11 Outline of Visualization Approaches
    12. Slide 12 What Makes a Good Infographic?
    13. Slide 13 Infographic
    14. Slide 14 Minerals Use in Safety Applications in the Workplace
    15. Slide 15 Mineral Resources
    16. Slide 16 Mobile App
    17. Slide 17 Minerals Infographic
    18. Slide 18 Mineral Tweets
    19. Slide 19 Elements of a Smartphone
    20. Slide 20 USGS Table in PDF
    21. Slide 21 The Toxic Twenty Infographic
    22. Slide 22 Geo-Time Travel with Time-Lapse
    23. Slide 23 Wind Map
    24. Slide 24 Mineral Commodity Summaries
    25. Slide 25 Spatiotemporal Data in a Bar Graph
    26. Slide 26 Gapminder Visualization
    27. Slide 27 Wind Farm Map
    28. Slide 28 Department of Energy MapBox
    29. Slide 29 Minerals Data Table in PDF
    30. Slide 30 D3 and Cesium Demo
    31. Slide 31 Google Maps Earth
    32. Slide 32 Produced Waters Map Viewer Application
    33. Slide 33 The National Broadband Map
    34. Slide 34 Example of a Table with Geospatial Data
    35. Slide 35 Example of a Simple Interactive Map
    36. Slide 36 Map with Special Symbology
    37. Slide 37 Example of a Map Generated Using MapBox
    38. Slide 38 Geospatial Storytelling
    39. Slide 39 Copper
    40. Slide 40 Big Holes
    41. Slide 41 Static Map for Large Poster
    42. Slide 42 Esri Story Map 1
    43. Slide 43 Table of Hydraulic Fracturing
    44. Slide 44 Esri Story Map 2
    45. Slide 45 Exploring Interactive Visualization
    46. Slide 46 Large Matrix Table
    47. Slide 47 Esri Story Map 3
    48. Slide 48 Mineral Map Needing Color
    49. Slide 49 Table of Mineral Commodities
    50. Slide 50 Combining Map andTable
    51. Slide 51 Table Referencing Spatial Regions
    52. Slide 52 Pollution Burdens
    53. Slide 53 Example of Stacked Line Graphs
    54. Slide 54 Interactive Line Graph Interface
    55. Slide 55 Use the D3 Javascript Library to Create Interactive Graphs
    56. Slide 56 Mineral Resources On-Line Spatial Data 1
    57. Slide 57 Mineral Resources On-Line Spatial Data 2
    58. Slide 58 World Energy Survey Analysis TIBCO Spotfire
    59. Slide 59 Mobile and Web Apps
    60. Slide 60 Mineral Resource Online Data Catalog 1
    61. Slide 61 Pttrns
    62. Slide 62 NASA Earth-Now
    63. Slide 63 Challenge.gov toxicSlayar
    64. Slide 64 Mineral Resource Online Data Catalog 2
    65. Slide 65 USGS Toxic Substances Website
    66. Slide 66 Climate Change Impacts in the United States PDF Report
    67. Slide 67 Climate Change Impacts in the United States Website
    68. Slide 68 Pathway Towards Engaging Crowds
    69. Slide 69 What is Worth Highlighting
    70. Slide 70 EMEH Data Formats
    71. Slide 71 The Value of a Good API
    72. Slide 72 EM-EH Challenges & Hackathons
    73. Slide 73 Crowdsourcing / Geo-Hacking
    74. Slide 74 Civic Hacking Goals
    75. Slide 75 Potential Visualization Tools
    76. Slide 76 What I Need From You
    77. Slide 77 Positives of Civic Hacking
    78. Slide 78 Questions?
  5. USGS Releases Data Management Instructional Memos
    1. Scientific Data Management Foundation
    2. Metadata for Scientific Data, Software, and Other Information Products
    3. Review and Approval of Scientific Data for Release 
    4. Preservation Requirements for Digital Scientific Data 
  6. Mineral Commodity Summaries 2015
    1. Cover Page
    2. Inside Cover Page
    3. Other Information
      1. INSTANT INFORMATION
      2. KEY PUBLICATIONS
      3. WHERE TO OBTAIN PUBLICATIONS
    4. General
      1. Introduction
      2. Growth Rates of Leading and Coincident Indexes for Mineral Products
      3. The Role of Nonfuel Minerals in the U.S. Economy
      4. 2014 U.S. Net Import Reliance for Selected Nonfuel Mineral Materials
      5. Significant Events, Trends, and Issues
        1. Figure 1 Major Metal-Producing Areas
        2. Figure 2 Major Industrial Mineral-Producing Areas Part I
        3. Table 1 U.S. Mineral Industry Trends
        4. Table 2 U.S. Mineral-Related Economic Trends
        5. Figure 3 Major Industrial Mineral-Producing Areas Part II
        6. Table 3 Value of Nonfuel Mineral Production in the United States and Principal Nonfuel Minerals Produced in 2014 p, 1
      6. Appendix A—Abbreviations and Units of Measure
      7. Appendix B—Definitions of Selected Terms Used in This Report
        1. Terms Used for Materials in the National Defense Stockpile and Helium Stockpile
        2. Depletion Allowance
      8. Appendix C—Reserves and Resources
        1. Part A—Resource/Reserve Classification for Minerals1
          1. Introduction
          2. Resource-Preserving Definitions
          3. Figure 1 Major Elements of Mineral-Resource Classification, Excluding Reserve Base and Inferred Reserve Base
          4. Figure 2 Reserve Base and Inferred Reserve Base Classification Categories
        2. Part B—Sources of Reserve Data
      9. Appendix D—Country Specialists Directory
        1. Africa and the Middle East
        2. Asia and the Pacific
        3. Europe and Central Eurasia
        4. North America, Central America, and the Caribbean
        5. South America
        6. Country specialist, Telephone, & E-mail
    5. Mineral Commodities
      1. Abrasives (Manufactured)
        1. Table Salient Statistics—United States
        2. Table Tariff Item
        3. Table World Capacity Production
      2. Aluminum
      3. Antimony
      4. Arsenic
      5. Asbestos
      6. Barite
      7. Bauxite and Alumina
      8. Beryllium
      9. Bismuth
      10. Boron
      11. Bromine
      12. Cadmium
      13. Cement
      14. Cesium
      15. Chromium
      16. Clays
      17. Cobalt
      18. Copper
      19. Diamond (Industrial)
      20. Diatomite
      21. Feldspar
      22. Fluorspar
      23. Gallium
      24. Garnet (Industrial)
      25. Gemstones
      26. Germanium
      27. Gold
      28. Graphite (Natural)
      29. Gypsum
      30. Helium
      31. Indium
      32. Iodine
      33. Iron and Steel
      34. Iron and Steel Scrap
      35. Iron and Steel Slag
      36. Iron Ore
      37. Iron Oxide Pigments
      38. Kyanite and Related Minerals
      39. Lead
      40. Lime
      41. Lithium
      42. Magnesium Compounds
      43. Magnesium Metal
      44. Manganese
      45. Mercury
      46. Mica (Natural)
      47. Molybdenum
      48. Nickel
      49. Niobium (Columbium)
      50. Nitrogen (Fixed)—Ammonia
      51. Peat
      52. Perlite
      53. Phosphate Rock
      54. Platinum-Group Metals
      55. Potash
      56. Pumice and Pumicite
      57. Quartz Crystal (Industrial)
      58. Rare Earths
      59. Rhenium
      60. Rubidium
      61. Salt
      62. Sand and Gravel (Construction)
      63. Sand and Gravel (Industrial)
      64. Scandium
      65. Selenium
      66. Silicon
      67. Silver
      68. Soda Ash
      69. Stone (Crushed)
      70. Stone (Dimension)
      71. Strontium
      72. Sulfur
      73. Talc and Pyrophyllite
      74. Tantalum
      75. Tellurium
      76. Thallium
      77. Thorium
      78. Tin
      79. Titanium and Titanium Dioxide
      80. Titanium Mineral Concentrates
      81. Tungsten
      82. Vanadium
      83. Vermiculite
      84. Wollastonite
      85. Yttrium
      86. Zeolites (Natural)
      87. Zinc
      88. Zirconium and Hafnium
  7. National Geochemical Survey Database
  8. Mineral Resources Data System (MRDS)
  9. NEXT

  1. Story
    1. Narrative
    2. Slides
      1. Slide 1 Data Science for USGS Minerals Big Data
      2. Slide 2 Evolution at the USGS
      3. Slide 3 USGS Mineral Resources Program (MRP)
      4. Slide 4 USGS Commodity Statistics and Information
      5. Slide 5 Adobe Acrobat Convert From PDF Tool
      6. Slide 6 Adobe Acrobat Convert From PDF to Excel
      7. Slide 7 Mineral Resources On-Line Spatial Data: National Geochemical Survey Database
      8. Slide 8 Mineral Resources On-Line Spatial Data: Mineral Resources Data System (MRDS)
      9. Slide 9 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Index
      10. Slide 10 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Attachments
      11. Slide 11 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Find
      12. Slide 12 Data Science for USGS Minerals Big Data: Excel Knowledge Base Find
      13. Slide 13 Data Science for USGS Minerals Big Data: Spotfire Cover Page
      14. Slide 14 Data Science for USGS Minerals Big Data: Minerals Commodity Summaries 2015 Tables in Spotfire
      15. Slide 15 Data Science for USGS Minerals Big Data: MRDS-shp in Spotfire
      16. Slide 16 Some Conclusions and Recommendations
  2. Spotfire Dashboard
  3. Research Notes
    1. MRP Science & Information Forum
      1. Program Schedule
        1. Tuesday, May 5
        2. Wednesday, May 6
        3. Thursday, May 7
      2. Poster Presentations
    2. Resources
    3. Email
  4. Slides
    1. Slide 1 Making the Story Behind USGS EM-EH Data Come Alive
    2. Slide 2 Chinese Proverb
    3. Slide 3 Tables with Spatial & Temporal Data
    4. Slide 4 Dense Static Maps
    5. Slide 5 USGS Energy, Minerals, and Environmental Health Projects
    6. Slide 6 Energy Resources Program (ERP)
    7. Slide 7 Mineral Resources Program (MRP)
    8. Slide 8 Environmental Health Program (EHP)
    9. Slide 9 Science and Decisions Center (SDC)
    10. Slide 10 The Rise of Public Engagement
    11. Slide 11 Outline of Visualization Approaches
    12. Slide 12 What Makes a Good Infographic?
    13. Slide 13 Infographic
    14. Slide 14 Minerals Use in Safety Applications in the Workplace
    15. Slide 15 Mineral Resources
    16. Slide 16 Mobile App
    17. Slide 17 Minerals Infographic
    18. Slide 18 Mineral Tweets
    19. Slide 19 Elements of a Smartphone
    20. Slide 20 USGS Table in PDF
    21. Slide 21 The Toxic Twenty Infographic
    22. Slide 22 Geo-Time Travel with Time-Lapse
    23. Slide 23 Wind Map
    24. Slide 24 Mineral Commodity Summaries
    25. Slide 25 Spatiotemporal Data in a Bar Graph
    26. Slide 26 Gapminder Visualization
    27. Slide 27 Wind Farm Map
    28. Slide 28 Department of Energy MapBox
    29. Slide 29 Minerals Data Table in PDF
    30. Slide 30 D3 and Cesium Demo
    31. Slide 31 Google Maps Earth
    32. Slide 32 Produced Waters Map Viewer Application
    33. Slide 33 The National Broadband Map
    34. Slide 34 Example of a Table with Geospatial Data
    35. Slide 35 Example of a Simple Interactive Map
    36. Slide 36 Map with Special Symbology
    37. Slide 37 Example of a Map Generated Using MapBox
    38. Slide 38 Geospatial Storytelling
    39. Slide 39 Copper
    40. Slide 40 Big Holes
    41. Slide 41 Static Map for Large Poster
    42. Slide 42 Esri Story Map 1
    43. Slide 43 Table of Hydraulic Fracturing
    44. Slide 44 Esri Story Map 2
    45. Slide 45 Exploring Interactive Visualization
    46. Slide 46 Large Matrix Table
    47. Slide 47 Esri Story Map 3
    48. Slide 48 Mineral Map Needing Color
    49. Slide 49 Table of Mineral Commodities
    50. Slide 50 Combining Map andTable
    51. Slide 51 Table Referencing Spatial Regions
    52. Slide 52 Pollution Burdens
    53. Slide 53 Example of Stacked Line Graphs
    54. Slide 54 Interactive Line Graph Interface
    55. Slide 55 Use the D3 Javascript Library to Create Interactive Graphs
    56. Slide 56 Mineral Resources On-Line Spatial Data 1
    57. Slide 57 Mineral Resources On-Line Spatial Data 2
    58. Slide 58 World Energy Survey Analysis TIBCO Spotfire
    59. Slide 59 Mobile and Web Apps
    60. Slide 60 Mineral Resource Online Data Catalog 1
    61. Slide 61 Pttrns
    62. Slide 62 NASA Earth-Now
    63. Slide 63 Challenge.gov toxicSlayar
    64. Slide 64 Mineral Resource Online Data Catalog 2
    65. Slide 65 USGS Toxic Substances Website
    66. Slide 66 Climate Change Impacts in the United States PDF Report
    67. Slide 67 Climate Change Impacts in the United States Website
    68. Slide 68 Pathway Towards Engaging Crowds
    69. Slide 69 What is Worth Highlighting
    70. Slide 70 EMEH Data Formats
    71. Slide 71 The Value of a Good API
    72. Slide 72 EM-EH Challenges & Hackathons
    73. Slide 73 Crowdsourcing / Geo-Hacking
    74. Slide 74 Civic Hacking Goals
    75. Slide 75 Potential Visualization Tools
    76. Slide 76 What I Need From You
    77. Slide 77 Positives of Civic Hacking
    78. Slide 78 Questions?
  5. USGS Releases Data Management Instructional Memos
    1. Scientific Data Management Foundation
    2. Metadata for Scientific Data, Software, and Other Information Products
    3. Review and Approval of Scientific Data for Release 
    4. Preservation Requirements for Digital Scientific Data 
  6. Mineral Commodity Summaries 2015
    1. Cover Page
    2. Inside Cover Page
    3. Other Information
      1. INSTANT INFORMATION
      2. KEY PUBLICATIONS
      3. WHERE TO OBTAIN PUBLICATIONS
    4. General
      1. Introduction
      2. Growth Rates of Leading and Coincident Indexes for Mineral Products
      3. The Role of Nonfuel Minerals in the U.S. Economy
      4. 2014 U.S. Net Import Reliance for Selected Nonfuel Mineral Materials
      5. Significant Events, Trends, and Issues
        1. Figure 1 Major Metal-Producing Areas
        2. Figure 2 Major Industrial Mineral-Producing Areas Part I
        3. Table 1 U.S. Mineral Industry Trends
        4. Table 2 U.S. Mineral-Related Economic Trends
        5. Figure 3 Major Industrial Mineral-Producing Areas Part II
        6. Table 3 Value of Nonfuel Mineral Production in the United States and Principal Nonfuel Minerals Produced in 2014 p, 1
      6. Appendix A—Abbreviations and Units of Measure
      7. Appendix B—Definitions of Selected Terms Used in This Report
        1. Terms Used for Materials in the National Defense Stockpile and Helium Stockpile
        2. Depletion Allowance
      8. Appendix C—Reserves and Resources
        1. Part A—Resource/Reserve Classification for Minerals1
          1. Introduction
          2. Resource-Preserving Definitions
          3. Figure 1 Major Elements of Mineral-Resource Classification, Excluding Reserve Base and Inferred Reserve Base
          4. Figure 2 Reserve Base and Inferred Reserve Base Classification Categories
        2. Part B—Sources of Reserve Data
      9. Appendix D—Country Specialists Directory
        1. Africa and the Middle East
        2. Asia and the Pacific
        3. Europe and Central Eurasia
        4. North America, Central America, and the Caribbean
        5. South America
        6. Country specialist, Telephone, & E-mail
    5. Mineral Commodities
      1. Abrasives (Manufactured)
        1. Table Salient Statistics—United States
        2. Table Tariff Item
        3. Table World Capacity Production
      2. Aluminum
      3. Antimony
      4. Arsenic
      5. Asbestos
      6. Barite
      7. Bauxite and Alumina
      8. Beryllium
      9. Bismuth
      10. Boron
      11. Bromine
      12. Cadmium
      13. Cement
      14. Cesium
      15. Chromium
      16. Clays
      17. Cobalt
      18. Copper
      19. Diamond (Industrial)
      20. Diatomite
      21. Feldspar
      22. Fluorspar
      23. Gallium
      24. Garnet (Industrial)
      25. Gemstones
      26. Germanium
      27. Gold
      28. Graphite (Natural)
      29. Gypsum
      30. Helium
      31. Indium
      32. Iodine
      33. Iron and Steel
      34. Iron and Steel Scrap
      35. Iron and Steel Slag
      36. Iron Ore
      37. Iron Oxide Pigments
      38. Kyanite and Related Minerals
      39. Lead
      40. Lime
      41. Lithium
      42. Magnesium Compounds
      43. Magnesium Metal
      44. Manganese
      45. Mercury
      46. Mica (Natural)
      47. Molybdenum
      48. Nickel
      49. Niobium (Columbium)
      50. Nitrogen (Fixed)—Ammonia
      51. Peat
      52. Perlite
      53. Phosphate Rock
      54. Platinum-Group Metals
      55. Potash
      56. Pumice and Pumicite
      57. Quartz Crystal (Industrial)
      58. Rare Earths
      59. Rhenium
      60. Rubidium
      61. Salt
      62. Sand and Gravel (Construction)
      63. Sand and Gravel (Industrial)
      64. Scandium
      65. Selenium
      66. Silicon
      67. Silver
      68. Soda Ash
      69. Stone (Crushed)
      70. Stone (Dimension)
      71. Strontium
      72. Sulfur
      73. Talc and Pyrophyllite
      74. Tantalum
      75. Tellurium
      76. Thallium
      77. Thorium
      78. Tin
      79. Titanium and Titanium Dioxide
      80. Titanium Mineral Concentrates
      81. Tungsten
      82. Vanadium
      83. Vermiculite
      84. Wollastonite
      85. Yttrium
      86. Zeolites (Natural)
      87. Zinc
      88. Zirconium and Hafnium
  7. National Geochemical Survey Database
  8. Mineral Resources Data System (MRDS)
  9. NEXT

Story

Slides

Data Science for USGS Minerals Big Data

Narrative

Years ago when I served a detail to the USGS, they were organized into the following divisions:

  • Geology
  • Water
  • Biology
  • Mapping

Now they are organized into the following:

  • Ecosystems
  • Climate and Land-Use Change
  • Natural Hazards
  • Water
  • Energy and Minerals, and Environmental Health
  • Core Science Systems

with a focus on Start with Science.

Recently, Dr. Sophia B. Liu, a Mendenhall Postdoc Fellow at the USGS, attended our Federal Big Data Working Group Meetups, and said:

Thank you for the amazing work you do in growing and sustaining the Federal Big Data Working Group meetup. I am very interested in exploring ways to collaborate and participate more directly in this meetup and use the technologies discussed at this meetup.

You mentioned you received some USGS data that you would like to talk about. Please send me more information and I would love to get a conversation and group of USGS folks more involved in these innovative efforts to make our data more engaging and interactive.

I also thought I would share a PPT presentation I am working on intended to present to those I am working with at USGS with the Energy, Minerals, and Environmental Health mission areas. I provide a narration of what I say for each slide in the Notes section with links to the examples. When you are in presenter view, you can also click on the screenshots to directly link to the website as well.

I replied: 

Excellent slides! I see we are both thinking about Data Science Data Publications, like the recent White House Climate Change Report PDF, which I did recently for a Meetup. Please see Data Science for Climate Change

Please suggest a recent Energy, Minerals, and Environmental Health Report (s) and Database (s) we can collaborate on for a Meetup in say mid-June.

I did some research on the USGS Mineral Resources Program (MRP) and found it: provides scientific information for objective resource assessments and unbiased research results on mineral potential, production, consumption, and environmental effects. The MRP is the sole Federal source for this information.

I also recently received the USGS Data Management Instructional Memos:

  • Scientific Data Management Foundation
  • Metadata for Scientific Data, Software, and Other Information Products
  • Review and Approval of Scientific Data for Release 
  • Preservation Requirements for Digital Scientific Data

These requirements are met with the Federal Big Data Working Group Meetups Data Science Data Publication done here.

I data mined for a major minerals report in PDF and major (big) databases and found:

The first two I converted to MindTouch and Excel using the Adobe Acrobat Convert From PDF Tooland the last two I imported into Spotfire, which has provided a demo of the World Energy Analysis. The conversion of the 85 minerals commodity PDFs to Excel was not successful.

The results are documented in the Slides below.

Some conclusions and recommendations are:

  • The USGS has evolved to Starting with Science so I started with Data Science for USGS Minerals Big Data.
  • I data mined the USGS Mineral Resources Program (MRP), the USGS Commodity Statistics and Information, and the Mineral Resources On-Line Spatial Data.
  • I converted PDF to MindTouch and Excel Knowledge Bases and used Spotfire for analytics and visualizations.
  • The result is a Data Science Data Publication. The USGS has many more PDF publications and data sets that could be Data Science Data Publications.

See Data Science for USGS Minerals Big Data Meetup, June 15, 2015.

Slides

Slides

Slide 2 Evolution at the USGS

http://www.usgs.gov/start_with_science/

BrandNiemann06152015Slide2.PNG

Slide 3 USGS Mineral Resources Program (MRP)

http://minerals.usgs.gov/minerals/pubs/mcs/

BrandNiemann06152015Slide3.PNG

Slide 4 USGS Commodity Statistics and Information

http://minerals.usgs.gov/minerals/pubs/commodity/

BrandNiemann06152015Slide4.PNG

Slide 5 Adobe Acrobat Convert From PDF Tool

https://cloud.acrobat.com/exportpdf

BrandNiemann06152015Slide5.PNG

Slide 6 Adobe Acrobat Convert From PDF to Excel

http://semanticommunity.info/%40api/...?origin=mt-web

BrandNiemann06152015Slide6.PNG

Slide 7 Mineral Resources On-Line Spatial Data: National Geochemical Survey Database

http://mrdata.usgs.gov/geochem/

BrandNiemann06152015Slide7.PNG

Slide 8 Mineral Resources On-Line Spatial Data: Mineral Resources Data System (MRDS)

http://mrdata.usgs.gov/mrds/

BrandNiemann06152015Slide8.PNG

Slide 9 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Index

http://semanticommunity.info/Data_Sc...erals_Big_Data

BrandNiemann06152015Slide9.PNG

Slide 10 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Attachments

http://semanticommunity.info/@api/de...2015Slide9.PNG

BrandNiemann06152015Slide10.PNG

Slide 11 Data Science for USGS Minerals Big Data: MindTouch Knowledge Base Find

http://semanticommunity.info/Data_Sc...erals_Big_Data

BrandNiemann06152015Slide11.PNG

Slide 12 Data Science for USGS Minerals Big Data: Excel Knowledge Base Find

http://semanticommunity.info/%40api/...?origin=mt-web

BrandNiemann06152015Slide12.PNG

Slide 13 Data Science for USGS Minerals Big Data: Spotfire Cover Page

BrandNiemann06152015Slide13.PNG

Slide 14 Data Science for USGS Minerals Big Data: Minerals Commodity Summaries 2015 Tables in Spotfire

BrandNiemann06152015Slide14.PNG

Slide 15 Data Science for USGS Minerals Big Data: MRDS-shp in Spotfire

BrandNiemann06152015Slide15.PNG

Slide 16 Some Conclusions and Recommendations

BrandNiemann06152015Slide16.PNG

MORE TO FOLLOW

Spotfire Dashboard

For Internet Explorer Users and Those Wanting Full Screen Display Use: Web Player Get Spotfire for iPad App

Error: Embedded data could not be displayed. Use Google Chrome

Research Notes

MRP Science & Information Forum

PDF

Program Schedule

May 5-7, 2015
USGS National Center, J.W. Powell Building
12201 Sunrise Valley Dr.
Reston VA 20192

 

Time Topic Location
Tuesday, May 5
   
9:00 am - 12:00 pm Leadership Training: High Performance Teams (pre-selected participation) Visitor’s Center (1C400)
12:00 pm– 1:30 pm Poster set up – Registration – Lunch
Art Hallway / Auditorium Area / Cafeteria
 
1:30 pm - 1:45 pm Welcome and Opening Remarks: Suzette Kimball, Larry Meinert Dallas Peck Auditorium
1:45 pm - 2:30 pm Plenary Session 1:
Panel Discussion – MRP Science and Information: Who needs it and what do they want?
Panel: L. Meinert (moderator), S. Kimball, H. Thorleifson, J. Thompson, R. Deery
Dallas Peck Auditorium
2:30 pm - 5:30 pm Poster Session 1 – Projects focused on:
- Assessment of Undiscovered Mineral Resources
- Characterization of the Midcontinent Rift and Related Mineral Resources
- Geophysics and Remote Sensing: State-of-the-art tools for understanding mineral resource potential
Art Hallway/ Auditorium Stage Area
2:30 pm - 4 :00 pm Breakout Session 1: Future Directions in Environmental and Exploration Geochemistry Visitor’s Center (1C400)
4:00 pm - 5:30 pm Breakout Session 2: Future Directions in Analytical and Isotope Geochemistry 1B215
6:00 pm - 8:00 pm Welcome Reception Sheraton Herndon/Dulles
Wednesday, May 6
   
8:00 am - 9:00 am Plenary Session 2: National-scale Efforts in Cooperation with Others
- Soil Geochemical Landscapes Project – D. Smith
- USMIN – A New National Mineral Resource Database – G. Fernette
Dallas Peck Auditorium
9:00 am - 12:00 pm Poster Session 2 – Projects focused on:
- Geologic and Mineral Resource Studies in Alaska
- Characterization and Identification of Critical Mineral Resources
Art Hallway/ Auditorium Stage Area
9:00 am - 10:30 am Breakout Session 3: Future Directions in Remote Sensing Visitor’s Center (1C400)
10:30 am - 12:00 pm Breakout Session 4: Future Directions in Geostatistical and Spatial Analysis of Data 1B215
12:00 pm - 1:00 pm Lunch Cafeteria
1:00 pm - 2:00 pm Plenary Session 3: Communicating Your Science – M. Jarvis, A.B Wade, T. Wood Dallas Peck Auditorium
2:00 pm - 5:00 pm Poster Session 3 – Projects focused on:
- Labs/Analytical Research & Development and Support
- Data Inventory and Delivery
Art Hallway/ Auditorium Stage Area
2:00 pm - 3:30 pm Breakout Session 5: Future Directions in Economic Geology Visitor’s Center (1C400)
3:30 pm - 5:00 pm Breakout Session 6: Future Directions in Mineral Resource Assessments 1B215
5:00 pm - 5:30 pm Plenary Session 4: Open Innovation: Engaging Citizens to Enhance Science in the Networked World – S. Liu Dallas Peck Auditorium
Thursday, May 7
   
8:00 am - 9:00 am Plenary Session 5: Minerals Information and Supply Chain Analysis (SCA)
- National Mineral Information Center (NMIC): Overview and New Directions – S. Fortier
- SCA Projects – Past, Present and Future –M. Magyar
Dallas Peck Auditorium
9:00 am - 12:00 pm Poster Session 4 – Projects focused on:
- Mineral Resources and the Environment
- Data Analysis & IT Management
- Outreach & Communication
Art Hallway/ Auditorium Stage Area
9:00 am - 10:30 am Breakout Session 7: Future Research in Alaska Visitor’s Center (1C400)
10:30 am – 12:00 pm Breakout Session 8: Future Directions in Minerals Information and Supply Chain Analysis 1B215
12:00 pm - 1:00 pm Lunch Cafeteria
1:00 pm – 4:00 pm Poster Session 5 – Projects focused on:
- Minerals Information & Supply Chain Analysis
- Mineral Resource Research and Information
Art Hallway/ Auditorium Stage Area
1:00 pm – 2:30 pm Breakout Session 9: Future Directions in Geophysics Visitor’s Center (1C400)
2:30 pm – 4:00 pm Breakout Session 10: Integrating Crowdsourcing, Citizen Science, and Civic Hacking to Enhance MRP Science 1B215
4:00 pm – 5:00 pm Plenary Session 6: 75 Years of Experience: the past, present and future of USGS economic geology – J. Slack & R. Goldfarb (moderated by L. Meinert) Dallas Peck Auditorium

Poster Presentations


*Themes
AK: Geologic and Mineral Resource Studies in Alaska
CM: Characterization and Identification of Critical Mineral Resources
DAITM: Data Analysis & IT Management
DID: Data Inventory and Delivery
Lab/R&D: Labs/Analytical Research & Development and Support
ME: Mineral Resources and the Environment
MI/SCA: Minerals Information and Supply Chain Analysis
MRA: Assessment of Undiscovered Resources
MRR: Mineral Resource Research and Information
MRS: Characterization of the Midcontinent Rift and Related Mineral Resources
RS-GP: Geophysics and Remote Sensing: State-of-the-art tools for understanding mineral resource potential

 

PI Org Theme* Session Provisional Poster Title
Hammarstrom, J. EMERSC MRA 1 Global Mineral Resource Assessment


Mars, J

EMERSC MRA 1 Integration of Remote-Sensing Alteration Mapping and Regional Geochemistry into New Geospatial-statistical, Quantitative Mineral Resource Methods
Mihalasky, M GMEGSC MRA 1

Mineral Resource Assessments: The Past, Present and Future

Zurcher, L GMEGSC MRA/MRR 1 Relation Between Porphyry Copper Sites, Crustal Preservation Levels, and Amount of Exploration in Magmatic Belts of the Central Tethys Region
Zientek, M GMEGSC MRA/MRS/CM 1 Assessment of the Platinum-Group Element Resources in Mafic-Ultramafic Igneous Intrusions of the Midcontinent Rift System, Lake Superior Region
Drenth, B CGGSC MRS 1 Mineral Resource Potential of the Midcontinent Rift (Task 1)
Manning, A CGGSC MRS

1

Exploration geochemistry of covered mineral deposits in the northern Midcontinent
Woodruff, L EMERSC MRS 1 Mineral Resource Potential of the Midcontinent Rift (Task 2)
Minsley, B CGGSC RS-GP 1 Geophysical Methods Development


Finn, C

CGGSC RS-GP/CM 1 Advanced Geophysical Characterization of Layered Mafic and Ultramafic Intrusions
Hoefen, T CGGSC RS-GP/CM 1 Spectroscopic Investigations of REE Minerals for Use with Imaging, Laboratory and Core Scanning Spectrometers

McCafferty, A

CGGSC RS-GP/CM 1 Airborne Geophysics for Rare Earth Element Deposits
Ponce, D. GMEGSC RS-GP/CM 1 Geophysical Investigations of the Mountain Pass Carbonatite Terrane, California
Shah, A. CGGSC RS-GP/CM


1

Geophysical and Geochemical Approaches to Evaluating REE Potential in the Southeastern U.S
Bultman, M GMEGSC RS-GP/MRA 1 Innovative use of geophysical data for assessing concealed mineral resources

Bedrosian, P

CGGSC RS-GP/MRS 1 Whither the Mid-Continent Rift? - Tectonic-Scale Structures in the Midwestern US from EarthScope Magnetotelluric Modeling
Haeussler, P ASC-MR AK 2 Western Alaska Range Metallogeny and Tectonics
Jones, J ASC-MR AK 2 Alaska/Yukon Geophysical/Geologic Reconciliation of the Pericratonic Yukon-Tanana Terrane
Todd, E ASC-MR AK 2 Multiple source components of Western Alaska Range magmas during progressive accretion of the Wrangellia composite terrane and evolution of the southern Alaska margin
Wilson, F ASC-MR

AK

2 Alaska Geologic Map and Database
Taylor, C. CMERSC AK/CM 2 Bokan Mountain, REE Deposit, Alaska
Wilson, F ASC-MR AK/DID 2 Alaska Resource Data File (ARDF)
Kokaly, R CGGSC AK/RS-GP 2 Hyperspectral Remote Sensing Data and a Multi-Proxy Investigation for Characterizing Mineral Resources Deposits in Alaska
Smith, B CGGSC AK/RS-GP 2 Alaska Geophysical Survey Interpretation
Box, S. GMEGSC CM 2 Yellow Pine antimony-gold deposits (central Idaho)
Foley, N. EMERSC

CM

2 Unconventional Resources of Rare Elements: The Bearing of Source and Process on the Genesis of Residual Deposits
Kelley, K. CMERSC CM 2 Critical Metals in Black Shales
Rytuba, J. GMEGSC CM 2 Rare earth element unconventional resources in high sulfidation systems
Slack, J. EMERSC CM 2 Setting and Origin of Iron Oxide-Cu-Co-Au-REE Deposits of Southeast Missouri (1)
Slack, J. EMERSC CM 2 Setting and Origin of Iron Oxide-Cu-Co-Au-REE Deposits of Southeast Missouri (2)
Verplanck, P. CMERSC CM 2 Fluids in REE Ore Genesis
Hayes, T. GMEGSC CM/AK 2 Alaska Critical Minerals Cooperative
Anderson, E CGGSC DID 3 National Geophysical Data Retrieval and Integration
Fernette, G. CMERSC DID 3 USMIN - The USGS Mineral Resource Database of the Future
Schweitzer, P. EMERSC DID 3 Mineral Resource Online Data Catalog
Smith, S. CMERSC

DID

3 National Geochemical Database II
Swayze, G CGGSC DID 3 USGS Digital Spectral Library
Ayuso, R. EMERSC Lab/R&D 3 Radiogenic and stable isotope methods
Azain, J. CMERSC Lab/R&D

3

Analytical Chemistry
Cosca, M CMERSC Lab/R&D 3 Argon Geochronology
Foster, A GMEGSC Lab/R&D 3 X-ray and Raman Spectroscopic Studies in Support of MRP Projects
Holm-Denoma, C CMERSC Lab/R&D 3 Technique development for in situ U-Pb dating and Pb-Sr isotopic analysis using LA-SC-ICPMS
Johnson, C CGGSC Lab/R&D 3 Isotope and Chemical Methods for Mineral and Geoenvironmental Assessments and Support of USGS Science Strategy
Koenig, A CMERSC Lab/R&D 3 Rapid Assessment of Rare and Critical Metals in Ore Deposits
Lowers, H CMERSC Lab/R&D

3

SEM Microprobe Laboratories
Verplanck, P CMERSC Lab/R&D 3 Non-Traditional Stable Isotopes
Wilson, S CGGSC Lab/R&D 3 Geologic Reference Materials
Wolf, R. CGGSC Lab/R&D

3

Geoanalytical Research Chemistry
Dunlap/Frost GMEGSC DAITM 4 Databases and Information Analysis (DIA)
Kress, T. EMERSC DAITM 4 EMERSC Computer and GIS Support
San Juan, C. CMERSC DAITM 4 CMERSC GIS and Information Management II
Shew, N ASC-MR DAITM 4 ASC-MR Databases and Information Analysis
Balistrieri, L GMEGSC ME 4 Modeling the potential toxicity of multiple metals (Cd, Co, Cu, Ni, Pb, Zn) associated with mineralized deposits
Goldhaber, M CGGSC ME 4 Regional Geologic Controls on Environmental and Human Health
Gray, F GMEGSC ME 4 Environmental Assessment of Selected Watersheds in the Patagonia Mountains, SE Arizona
Long, K GMEGSC ME 4 Role of Geology and Geochemistry in Assessing Potential Environmental Performance of Alternative Sources of Rare Earth Elements
Morrison, J. CGGSC ME 4 Processes controlling groundwater quality in uranium ISR mining
Piatak, N EMERSC ME 4 Slag: Valuable Resource or Environmental Liability?
Plumlee, G CGGSC ME 4 Metal and Mineral Commodities in the Built and Waste Stream Environments
Plumlee, G CGGSC ME 4 Minerals and Health - Environmental Disaster Response
Smith, D. CMERSC

ME

4 Soil Geochemical Landscapes of the Conterminous United States
Holloway, J. CGGSC ME/CM 4 Mercury and Arsenic Mobility from the Cinnabar Mine Site, Yellow Pine Mining District, Idaho
Seal, R EMERSC ME/MRS 4 Environmental Geochemistry to Evaluate Risks Associated with Past and Future Mining in the Lake Superior Region
Liu, S. EMEH O/C 4 Adaptation of the Crisis Crowdsourcing Framework: Strategically Designing an Integrated Crowdsourcing System for the Mineral Resources Domain
Baker, M NMIC MI/SCA 5 Global Facilities Database
Bermudez-Lugo, O. NMIC MI/SCA 5 Ebola Virus Outbreak and the Mineral Industries of Guinea, Liberia, and Sierra Leone
Gambogi, J NMIC MI/SCA 5 DLA-Defense National Stockpile Support
Sangine, E. NMIC MI/SCA 5 Conflict Minerals, Dodd Frank, and 3T+G (tin, tantalum, tungsten & gold)
Wacaster, S. NMIC MI/SCA 5 Mining, Mineral Processing, and Extraction Industries of Cuba - Historical Perspective and Current Status
Xun, Sean NMIC MI/SCA 5 Methodology for Determining Critical and Strategic Material Criticality
Emsbo, P. CMERSC MRR 5 Paired δ88Sr - 87/86Sr systematics- a new frontier in ore genesis and assessment: evaluation and application in the US midcontinent
John, D GMEGSC MRR 5 Geology and hydrothermal systems of Miocene ancestral Cascade arc magmatism, Bodie Hills, California and Nevada
Lund, K CMERSC MRR 5 Basement domain map of the conterminous United States and Alaska
Mercer, C CMERSC MRR 5 Magmas to Metals: Melt Inclusion Insights into the Formation of Critical Element-Bearing Ore Deposits
Scheiderich, K CMERSC MRR 5 Applications of metal stable isotopes to minerals research
Scott, C EMERSC MRR 5 The Biogeochemistry of Sediment Hosted Ore Deposits
Stillings, L GMEGSC MRR 5 Chemistry and mineralogy of the high elevation playa lake sediments at Dasht-e-Nawar, Afghanistan
Taylor, R CMERSC MRR 5 California gold deposits; Grass Valley or regional geotectonic overview
Vikre, P GMEGSC MRR 5 Magmatic-tectonic history and component sources of major precious metal deposits in the southern Walker Lane
Wilson, A CMERSC MRR 5 Nonmetallic Resources of the U.S., with a Focus on Frac Sand Resources

Email

Excellent slides! I see we are both thinking about Data Science Data Publications, like the recent White House Climate Change Report PDF, which I did recently for a Meetup: http://semanticommunity.info/Data_Sc...Climate_Change

Please suggest a recent Energy, Minerals, and Environmental Health Report (s) and Database (s) we can collaborate on for a Meetup in say mid-June.

Thank you for the amazing work you do in growing and sustaining the Federal Big Data Working Group meetup. I am very interested in exploring ways to collaborate and participate more directly in this meetup and use the technologies discussed at this meetup.

You mentioned you received some USGS data that you would like to talk about. Please send me more information and I would love to get a conversation and group of USGS folks more involved in these innovative efforts to make our data more engaging and interactive.

I also thought I would share a PPT presentation I am working on intended to present to those I am working with at USGS with the Energy, Minerals, and Environmental Health mission areas. I provide a narration of what I say for each slide in the Notes section with links to the examples. When you are in presenter view, you can also click on the screenshots to directly link to the website as well.

Sophia B. Liu, Ph.D.               12201 Sunrise Valley Drive

U.S. Geological Survey          Mail Stop 913, Room 4A231

Mendenhall Postdoc Fellow   Reston, VA 20192-0002

Email: sophialiu@usgs.gov    @sophiabliu (social media)

Work:  703-648-6104              http://profile.usgs.gov/sophialiu

Cell:    630-729-4216              http://icoast.us

Slides

Slides

Slide 1 Making the Story Behind USGS EM-EH Data Come Alive

SophiaBLiu04092015Slide1.PNG

Slide 2 Chinese Proverb

I want to start with some words of wisdom, a Chinese proverb:
“Tell me and I’ll forget; show me and I may remember; involve me and I’ll understand.”

For you scientists, here are some statistics to confirm this ancient adage.
People only remember 10% of what they hear and 30% of what they read,
but about 80% of what they see and do.

What I hope to illustrate in this talk is why data visualizations are a valuable way to engage people in your science and how crowdsourcing is increasingly a way to engage the average citizen to participate and understand the value of your work.

http://www.quoteswave.com/picture-quotes/389541

SophiaBLiu04092015Slide2.PNG

Slide 3 Tables with Spatial & Temporal Data

Unfortunately much of how USGS communicates science is inefficient.

Many of the publications have a plethora of quantitative tables with spatial and temporal data hidden within them that could be conveyed through spatial and temporal visualizations

SophiaBLiu04092015Slide3.PNG

Slide 4 Dense Static Maps

Much of how we communicate our science is geared towards journal publications in PDF formats, resulting in static maps that try to show high-dimensional data but are limited in a two-dimensional space.

SophiaBLiu04092015Slide4.PNG

Slide 5 USGS Energy, Minerals, and Environmental Health Projects

Let me start with giving an overview of what I propose to focus on for each of the EM-EH projects.

SophiaBLiu04092015Slide5.PNG

Slide 6 Energy Resources Program (ERP)

For the Energy Resources Program, we will first focus on exploring different ways to visualize data from the Produced Waters Geochemical Database. The Groundwater Protection Council also announced its intent to roll out a new version of FracFocus 3.0.

The goal will be to develop visualizations of the water use and geochemicals related to hydraulic fracturing. We will also see if FracFocus 3.0 actually allows for general searches with results in machine readable formats, as they claim, and see if these data can be easily integrated into the Produced Waters Geochemical Database to develop a representative picture of hydraulic fracturing additives.

http://energy.usgs.gov/Environmental...x#3822349-data 
http://energy.usgs.gov/Tools/EnVisionSplash.aspx 
http://certmapper.cr.usgs.gov/data/energyvision/ 
https://fracfocus.org/ 

===

Explore how FracFocus 3.0 has made their data more accessible and if it addresses the data accessibility and quality challenges for integrating it into the USGS energy resources. "Uses include: compiling statistics on water use for hydraulic fracturing in different plays, developing a representative picture of hydraulic fracturing additives and spatial variance in their composition, using spud dates in wells to assess the relative age of newer wells within a play, and using it as a non-proprietary source of well depth, location, and API number data.”

SophiaBLiu04092015Slide6.PNG

Slide 7 Mineral Resources Program (MRP)

For the Mineral Resources Program (MRP), many of the datasets in the Mineral Resources Data System (MRDS) and the National Minerals Information Center (NMIC) are presented in its rawest form as long lists of quantitative tables, bar graphs, and static maps that are not easy to understand nor interpret immediately.

We will specifically explore ways of communicating the science in the Mineral Commodity Summaries and on Rare Earth Elements (REE) in new ways. The goal will be to increase user base and accessibility to MRDS and the NMIC products.

http://minerals.usgs.gov/ 

http://mrdata.usgs.gov/mrds/ 

http://minerals.usgs.gov/minerals/

SophiaBLiu04092015Slide7.PNG

Slide 8 Environmental Health Program (EHP)

For the Environmental Health Program (EHP), they are working on a Hurricane Sandy project that focuses on the development of a contaminant vulnerability network called Sediment Contaminant Resiliency and Response (SCoRR), which has resulted in collating and analyzing sediment contaminant data to determine the sources of toxic contamination particularly after Hurricane Sandy.

Primarily, we will focus on visualizing the data generated from the 2013 USGS report titled “Estuarine Bed-Sediment-Quality Data Collected in New Jersey and New York after Hurricane Sandy.”

The goal will be to identify stories and develop visualizations that explain the sources and impact of toxic contamination exposure after extreme storms like Hurricane Sandy.

http://toxics.usgs.gov/about.html 

http://pubs.usgs.gov/fs/2013/3091/ 

http://pubs.usgs.gov/ds/0905/ 

SophiaBLiu04092015Slide8.PNG

Slide 9 Science and Decisions Center (SDC)

For the Science and Decisions Center, we are working on two publications describing the value and application of citizen science at USGS in the form of a guidebook.

SophiaBLiu04092015Slide9.PNG

Slide 10 The Rise of Public Engagement

As we develop these publications, my goal with the other EM-EH projects is to explore how we can engage the public and interested volunteers to develop new technologies and applications for interpreting and visualizing the EM-EH data.

My plan is to engage known and unknown experts and interested citizens locally and nationally. Their mission will be to help create visualizations, maps, and stories to illustrate how EM-EH can communicate science in new ways using emerging visualization tools by engaging a wider community of interested citizens that want to help.

http://www2.epa.gov/innovation/feder...itizen-science

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Slide 11 Outline of Visualization Approaches

What I will do next is go through these six different visualization approaches: infographics, time-lapse visualizations, intuitive interactive maps, geospatial storytelling, interactive graphs, and designing web and mobile applications.

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Slide 12 What Makes a Good Infographic?

A good infographic considers these four elements of using reliable data effectively designed to tell a good story with a clear message that can be easily shared widely.

http://visual.ly/what-makes-good-infographic 

Infographics are visualizations of data that can help audiences quickly grasp complex sets of ideas. The key to a good infographic design is to find interesting and reliable data, then come up with an awesome blueprint and visual story to deliver the underlying message. Infographics have become an extremely popular form of content marketing that can reward a site with quality backlinks and tons of new traffic, but what separates the really good infographics from the rest?

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Slide 13 Infographic

I’m sure many of you have come across some cool infographics online. They all use basic design principles of strategically using lines, colors, shapes, and space in an efficient way to present complex information and concepts quickly and clearly.

http://paper-leaf.com/blog/2011/02/e...eference-sheet

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Slide 14 Minerals Use in Safety Applications in the Workplace

I know many of your programs are beginning to provide information products that show how USGS science is relevant to our daily lives, in this case how minerals are used for safety applications in our workplace.

These images of real-world applications are helpful because they all are familiar to us, but it is heavily loaded with textual information that requires time to read.

http://minerals.usgs.gov/minerals/pu...susesafety.pdf 

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Slide 15 Mineral Resources

Here is a good example of visualizing the Mineral science data in the context of our daily lives. I know this visualization was developed quite a long time ago, but you can see how the text is quite small to read and that there is just too much text to read in general.

http://pubs.usgs.gov/of/2001/0360/pdf/of01-360.pdf 

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Slide 16 Mobile App

This mobile app in our very own lobby at USGS in Reston is a move towards connecting certain minerals to specific products we have in our own homes.

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Slide 17 Minerals Infographic

I came across this infographic when I was looking for visualizations related to minerals.

I like how it uses a tree ring pattern to indicate time, but you can see how it is a bit hard to digest and quickly interpret.

The font size is quite small and there are multiple types of graphs all combined in one space. 

Still part of the underlying message of this infographic is communicating how many years these minerals will be left if the world or US consumes at today’s rate.

This directly relates to aspects of the Mineral Resource Lifecycle, which is of growing interest and concern for your programs.

http://www.sciencearchive.org.au/nov..._005image2.jpg

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Slide 18 Mineral Tweets

We now are living in a networked world with a decreasing attention span, where we are willing to watch a 5 minute YouTube video or read a 140 character tweet in Twitter, but dread having to read a 10 or 20 page paper.

There is value in thinking of a catchy headline to draw people into our rich and reliable science. For example, the tweet and articles surrounding how our poop and sewage is literally a goldmine of precious metals is definitely eye catching and can get a wider audience more interested in how USGS is trying to understand the resource lifecycle for many of our critical energy and mineral resources.

https://twitter.com/usgsminerals

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Slide 19 Elements of a Smartphone

Rare earth minerals and other critical minerals started to really become a hot topic as smartphones and energy efficient technologies became more popular over the past five years. 

And it is through these types of infographics that are helping to bring this science to the average citizen.

http://www.compoundchem.com/wp-conte...rtphone-v2.png 

http://www.compoundchem.com/2014/02/...-a-smartphone/ 

There are an isolated few graphics online that look at elements involved in the manufacture of a smartphone – for example, this ‘Periodic Table of iPhones’ – but there’s actually remarkably little easily accessible information out there that details the specific compounds used for specific purposes in mobile phones. This probably isn’t surprising since these details are probably kept under the lock and key of patent laws and the like; however, I tried my best with this graphic to provide a little more detail about specific uses, an undertaking that took a lot more effort than I initially expected!

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Slide 20 USGS Table in PDF

But as scientists, we tend to communicate our science to other scientists, which means we publish articles in journals that result in PDFs with graphs and tables like this.
 
Now I don’t mean to demean the robust nature and tremendous amount of effort that it took to generate these data, especially since USGS is renowned for providing reliable and reputable science. But we are also infamous for not making our data more accessible to a wider audience.
 
So in this table, the first column indicates a geospatial region. It might not always be necessary to convert tables like this into a map but at least it could be reordered in a way that may allude to a trend in what the quantitative findings reveal.
 

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Slide 21 The Toxic Twenty Infographic

For example, here is a nice, simple infographic showing the Top 20 states with the most toxic air pollution based on a report by The Natural Resources Defense Council in July 2011 and EPA’s Toxic Release Inventory reported for 2010.

It shows how much toxic emissions were released by each state, the sources of of the toxic emissions and what percentage they contribute, as well as the health risks associated with toxic air pollution.

What I like about this infographic is that it does not show too much data at once and also uses a nice balance of just a few colors, text, and images to convey the message with an easy mnemonic, The Toxic Twenty.

http://ctbythenumbers.info/files/201.../toxic-air.jpg 
Check out this infographic displaying the states with the most toxic air pollution according to The Natural Resources Defense Council. This graphic displays the “Toxic Twenty,” explains just how much of the nation faces the threats of toxic emissions, how we get those toxic emissions, and explains the health effects of this sort of pollution exposure. Transportation is only responsible for 18% of the toxic air pollution – the generation of electricity comes in first at 44%.

http://www.nrdc.org/media/2011/110720.asp 
The EPA’s Toxic Release Inventory, known as the TRI, is a national database of toxic emissions self-reported by industrial sources. Power plants report emissions of mercury, hydrochloric acid, and other hazardous metals. NRDC released the first “Toxic 20” report in July 2011. The analysis used publicly available data in the TRI to rank states by air pollution levels from 2009. Using the same methodology, today’s analysis compared TRI emissions reported for 2010 from the electric utilities sector to those from other sectors and ranked sources by total emissions by sector.  The analysis identifies top emitting power plants based on toxic emissions reported to TRI. For the full methodology, see the analysis “Toxic Power: How Power Plants Contaminate Our Air and States,” which can be found here: http://www.nrdc.org/air/toxic-power-presentation.asp

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Slide 22 Geo-Time Travel with Time-Lapse

Now let’s do a little time travel with some time-lapse visualizations.

What I want to show you are ways in which to bring alive the temporal side of geologic data.

All geo data has a temporal dimension.

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Slide 23 Wind Map

This is one of the most beautiful visualizations I have come across. This particular one goes back in time to when Hurricane Sandy made landfall.

But I also want to show you the home page of this Wind Map, which shows near real-time visualizations of surface wind data from the National Weather Service’s National Digital Forecast Database, which are near-term forecasts revised once per hour.

So what you see is a “living portrait” as the creator of this map calls it. It almost looks like the living veins of mother earth’s wind across the US.

Now I know much of EMEH data does not have a lot of real-time data, unless if we were to include more social media data.

http://hint.fm/wind/gallery/oct-30.js.html 
http://hint.fm/wind/index.html 

Uses NOAA’s National Weather Service National Digital Forecast Database.
The wind map is a personal art project, not associated with any company. We've done our best to make this as accurate as possible, but can't make any guarantees about the correctness of the data or our software. Please do not use the map or its data to fly a plane, sail a boat, or fight wildfires :-)  If the map is missing or seems slow, we recommend the latest Chrome browser. Surface wind data comes from the National Digital Forecast Database. These are near-term forecasts, revised once per hour. So what you're seeing is a living portrait. (See the NDFD site for precise details; our timestamp shows time of download.) And for those of you chasing top wind speed, note that maximum speed may occur over lakes or just offshore. If you're looking for a weather map, or just want more detail on the weather today, see these more traditional maps of temperature and wind. 

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Slide 24 Mineral Commodity Summaries

But USGS is known for conducting periodic assessments and providing a perspective in geologic time.

For example, the Mineral Resources program has an extensive list of Mineral Commodity Summaries from 1996 to 2015.

This is an impressive amount of data but there are literally hidden gems in these PDFs. 

http://minerals.usgs.gov/minerals/pubs/mcs/

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Slide 25 Spatiotemporal Data in a Bar Graph

Temporal data may often be hidden in graphs. In this case, both spatial and temporal data are all meshed into this small and static bar graph.

The x-axis are US states and then you have gradients of blue (hydraulic fractured wells) and red (hydraulic fracturing treatments) to indicate a range of years but are disproportionate in time spans: (a) 1947-1952, (b) 1953-1999, (c) 2000-2010.

So much spatiotemporal data is mashed up into this bar graph making it hard to interpret the underlying message and findings.

http://pubs.usgs.gov/sir/2014/5131/p...2014-5131.pdf# 

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Slide 26 Gapminder Visualization

To show you how to make spatiotemporal data come alive, Hans Rosling’s famous visualizations using Gapminder are an important place to start.

Have any of you seen his TED talk or Gapminder?

This is one of his datasets called “USA or China: Who emits the most CO2?”
You just press play and you can go back in time and compare how CO2 emissions from different countries changes over time.

You can also switch to the Map view to get a geographic replay of this data.

http://www.gapminder.org/world/#$maj..._r,,,,,,;i44_r,,,,,,

Few countries in history have managed to combine high income with low CO2-emissions per person.

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Slide 27 Wind Farm Map

Doug Duncan pointed out this Wind Farm map that USGS helped to build.

It is a really great map that I have to admit was much more seamless and easy to interact with than some of the other USGS EnergyVision maps I was exploring.

Still the problem that maps often suffer from is that they just become dots on a map.

There are some neat features on this WindFarm map, like being able to filter the data and see certain types of federal lands, but still, the filters were hard to interpret and interact with when I started to adjust them.

http://eerscmap.usgs.gov/windfarm/

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Slide 28 Department of Energy MapBox

The Department of Energy is leveraging a tool called MapBox to make it easier to consume their open data.

Here is an example of using probably the same or similar data but bringing it to life with a time lapse capability embedded within this map.

It’s no longer just dots on a map, but it also gives people a sense of some of the spatiotemporal trends.

http://energy.gov/maps/wind-farms-through-years#buttn

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Slide 29 Minerals Data Table in PDF

Here is another example of a table with a list of countries repeated for different dimensions of the data for 2011 and 2012.

Until you are an expert mineralogist that have become familiar with these tables and this style of presenting these data, it takes a significant amount of time and effort to interpret these tables and see any major trends or patterns.

http://minerals.usgs.gov/minerals/pu...2012-raree.pdf

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Slide 30 D3 and Cesium Demo

D3 and Cesium Demo: Cesium is a JavaScript library for creating 3D globes and 2D maps in a web browser without a plugin. It uses WebGL for hardware-accelerated graphics, and is cross-platform, cross-browser, and tuned for dynamic-data visualization. Cesium is open source under the Apache 2.0 license. It is free for commercial and non-commercial use. Alexander Wood and Ed Mackey from Analytical Graphics, Inc. developed an app that showcases the synergy between the powerful open source visualization frameworks, D3 and Cesium. This demo is the result of a one day hackathon hosted at Analytical Graphics, Inc in April of 2013. The app repurposed Mike Bostock’s D3 recreation of Hans Roslings’ “Health and Wealth of Nations” as an interactive overlay for a Cesium geospatial view. Geolocating each data point with its country of origin adds new context to the data. Hans Rosling’s original 2D visualization presents 4 dimensions of data, including income, population, and life expectancy for nations over the span of 200 years. The x axis represents income per capita and inflation adjusted (dollars), while the y axis represents life expectancy in years. A nation further to the right of the graph signifies that the people are wealthier. Similarly, a nation plotted higher up on the graph indicates the nation is healthier. The radius of each circle is tied to the population of the nation.
From a technical standpoint, this application demonstrates usage of key concepts for Cesium and integration with D3 visualizations.

These concepts are summarized below.
- Data presentation in Cesium’s 2.5D Columbus view
- Metrics rendered in Cesium using Polylines
- CesiumWidget functionality extended by individually incorporating SceneModePicker, Timeline Widget, Animation Widget, HomeButton Widget, and Fullscreen Widget
- Mouseover event handling to highlight a nation in both D3 chart & Cesium scene for cohesiveness btw data presentations
- Clicking on a nation, in either display, will construct a CameraFlightPath to fly the 3D camera in Cesium in for a closer look
- Loose coupling of these two visualizations via d3.dispatch for signaling events between presentation layers

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Slide 31 Google Maps Earth

People now have higher expectations when using interactive maps, especially as we increasingly use navigation apps everyday.

They want them to be as intuitive as Google Maps and not take a long time to load.

http://www.slideshare.net/APA-MA/goo...boration102111

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Slide 32 Produced Waters Map Viewer Application

This is the Produced Waters Map Viewer Application that shows 8 types of data points differentiated by color.

One of the main problems with this map is that when you try to zoom in or out of the map, this “Please wait…Extent change” pop up box appears, taking a significant amount of time for it to load and render the map.

This is also an example of the problem when you have too many dots on a map, making it hard to see or click on data points that are layered on top of each other.

http://eerscmap.usgs.gov/pwapp/

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Slide 33 The National Broadband Map

This is The National Broadband Map created by the Federal Communications Commission who used the OpenGeo Suite to leverage open source tools and design an open architecture around their data to allow anyone else to build similar maps.

It is a map that is easy to interact with, doesn’t take a long time to load when you zoom in and out of the map, and you can easily filter the data with this slider on top.

They also made it easy to switch between other related maps with this map gallery below.

http://www.broadbandmap.gov/technology 

http://boundlessgeo.com/case-study/fcc/ 

http://boundlessgeo.com/press-releas...opengeo-suite/

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Slide 34 Example of a Table with Geospatial Data

Here is another example of a table with geospatial data indicating certain locations where samples were taken, but you need a decoder to decipher the exact locations.

http://pubs.usgs.gov/ds/0905/support...-tables-07.pdf 

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Slide 35 Example of a Simple Interactive Map

Here is an example of a simple interactive map developed in just a few hours by an active contributor at Code for DC.

Each of the neighborhoods in DC could represent each of the site codes in the previous map.

With this type of map, all you have to do is roll over (not even click) each neighborhood and you can quickly and seamlessly get the statistics for that area.

You can also easily click on these filters to just show certain types of data on the map.

http://electionmap.wamu.org/ 
Developed by Chris Given, an active contributor at Code for DC

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Slide 36 Map with Special Symbology

Here is a map of those site locations, which definitely are hard to refer to by a place name, since they refer to a point rather than a polygon of a small area.

The design of the symbols for this map are an interesting way to try to use the circle shape of a dot to include four data features within them.

It’s almost similar to the fire diamond symbol indicating hazardous material. 

But, this approach can be limiting and hard to quickly see any patterns on this static map.

http://pubs.usgs.gov/ds/0905/support/pdf/ds905.pdf

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Slide 37 Example of a Map Generated Using MapBox

Here is an example of a map generated using MapBox, which shows the type of mobile device people are using when tweeting from Twitter across the world.

But you can also zoom into this map, such as in the DC area, and get a high-resolution view of each data point at a micro-scale.

So imagine each of these four device types labeled as the four types of screening data from the previous map.

You can easily switch them on and off and zoom in and out of the map to discover any geospatial patterns.

https://www.mapbox.com/labs/twitter-gnip/brands/# 

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Slide 38 Geospatial Storytelling

There has also been a rise in telling stories with maps by using a geographic interface to organize and present information.

These stories often combine interactive maps with rich content like text, photos, videos, and audio to create an intuitive user experience that is simple without requiring special knowledge or skills in GIS.

These stories tend to be designed for the general, non-technical audience to summarize complex issues in a simple way.

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Slide 39 Copper

I think we all strive to be a good storyteller but many USGS publications are geared towards a journal publication type of venue heavily loaded with texts and sometimes a handful of figures, graphs, and tables.

Here is an example of an excerpt from the Mineral Commodity Summary report on Copper referencing the Bingham Canyon Mine in Utah.

http://minerals.usgs.gov/minerals/pubs/mcs/

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Slide 40 Big Holes

Interestingly I found this Story Map, which is an Esri tool, that gives a guided a tour of the world’s largest surface mines.

It starts with an interactive map indicating each mine on the map around the world. 

When you scroll down, you get a tour of each mine.

This first one refers to the Bingham Canyon Mine and allows you to zoom in and out of the high-resolution satellite imagery of this mine to get an up-close and personal view of it.

Each mine has a short summary of text on the right, while allowing you to interactively zoom in and out to see the manmade scars of the mine on the left.

http://story.maps.arcgis.com/apps/Ma...bf81f9cc8adbd6

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Slide 41 Static Map for Large Poster

Here is a static map that was probably meant to be viewed as a large poster.

Each of these smaller boxes refers to certain regions across the US related to unconventional oil resources.

There is not a lot of detail within each of these boxes, but it is probably because it is too hard to add more information with the limited space in this 2D poster map.

http://pubs.usgs.gov/dds/dds-069/dds...-jj_plate1.pdf

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Slide 42 Esri Story Map 1

Here again is another example of an Esri Story Map where you can break up the data into these three or however many sections you want to allow users to interact with different types of data and also see the quantitative data associated with each geographic region.

http://storymaps.esri.com/stories/2013/energy/

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Slide 43 Table of Hydraulic Fracturing

Here is another example of a table with geospatial content indicating the locations of hydraulic fracturing.

http://pubs.usgs.gov/sir/2014/5131/p...2014-5131.pdf#

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Slide 44 Esri Story Map 2

Here is another example of an Esri Story Map with similar content allowing the user to get bite-size textual content on the left.

But the primary focus is the interactive map on the right that allows you to zoom in and out of locations as well as click on certain locations to get quantitative information about that region.

http://www.arcgis.com/apps/MapSeries...9c1b086b5b66b5 

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Slide 45 Exploring Interactive Visualization

Now what I also want to show you are examples of other kinds of interactive graphs that encourages the user to engage with the data, whether it be in a geospatial way, temporal way, or other filters you may have.

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Slide 46 Large Matrix Table

Here is an example of a table showing quite a large matrix of data combining locations of 13 regions twice, two types of classifications, and then percentages of land-use.

This table is really hard to quickly interpret.

The bolded percentages are an attempt at drawing attention to a particular trend.

But again this table could be designed in a way that contextualizes the data by leveraging its spatial and temporal dimensions.

http://pubs.usgs.gov/ds/0905/support...-tables-06.pdf

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Slide 47 Esri Story Map 3

Here is another Esri Story Map that uses a Swipe Tool to allow the user to quickly switch back and forth between different content across the same region.

You may be more familiar with seeing this tool to show temporal before and after satellite imagery of a storm or tornado.

You can also use this swipe tool to switch between different types of data in the same region as shown here.

http://storymaps.esri.com/stories/diabetes/

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Slide 48 Mineral Map Needing Color

Here is another example of a map where color could be used instead of the abbreviation of the mineral symbol to at least see any geospatial trends in a visual way.

http://minerals.usgs.gov/minerals/pu...15/mcs2015.pdf

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Slide 49 Table of Mineral Commodities

Here is a table that organizes the mineral commodities based on highest to lowest Net Import Reliance while indicating the countries associated with each import of that mineral commodity.

http://minerals.usgs.gov/minerals/pu...liance2014.gif

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Slide 50 Combining Map andTable

Now imagine combining the data from those two examples of the map and table and designing this type of interface.

Although an interactive map is available, you can show data for just the Top 10 or Bottom 10 on the map and also focus the interaction more on the percentages related to the data in these locations.

This creates a seamless interaction with the data and allows users to understand the complex dimensions of the data and how different datasets might interact together to reveal trends and unexpected patterns.

http://global-climatescope.org/en/ 
Development Seed Project
Like most of the sites we build, Climatescope is a fully interactive site without a database or a heavy CMS. Climatescope users can manipulate, interrogate, and download the data on any device and in low bandwidth requirements. The site uses Jekyll, Angular, and D3 and is hosted on Github. Read more on our approach to CMS-free websites. Customized weighting: People have different priorities when evaluating the environment for clean energy. The site is designed for a range of users, from activists to journalists, politicians, environmentalists, and the curious. FOMIN is committed to giving Climatescope users full control over how much weight each metric carries. To accomodate this, we built simple, intuitive sliders. Movement in one slider spreads the difference evenly across the other three factors. You can lock any slider to make it easier to hit an exact breakdown.

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Slide 51 Table Referencing Spatial Regions

Here is another example of a table referencing spatial regions and then types of contaminants and literature related to those contaminates in each of these regions.

http://pubs.usgs.gov/ds/0905/support/pdf/ds905.pdf

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Slide 52 Pollution Burdens

Here is an interactive map by the LA Times indicating certain regions within California color coded with a gradient from yellow to red that allows users to get more in depth quantitative information when you click on each region.

This map actually shows more relevant examples of data for the Environmental Health Program, like toxic releases and pesticide use.

But again this is a fairly easy to use map embedded in an online news article that allows you to access the quantitative analysis of each region while still switching between different datasets with these big filter buttons on the right side here.

http://graphics.latimes.com/responsi...ution-burdens/ 

http://oehha.ca.gov/ej/pdf/CES20Publ...ew04212014.pdf

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Slide 53 Example of Stacked Line Graphs

Here is an example of three line graphs stacked on top of each other to line up the time scale to see trends between 1947 and 2010 regarding hydraulic fracturing records, treatment fluid records, and additive records.

http://pubs.usgs.gov/sir/2014/5131/p...2014-5131.pdf#

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Slide 54 Interactive Line Graph Interface

Imagine trying to navigate that same data with this type of interactive line graph interface, which uses the D3 javascript library.

It is a bit more engaging for the user.

It is a very slick tool where if it is designed well enough then you can allow the user to more easily see trends and unexpected patterns.

http://www.nytimes.com/interactive/2...tory.html?_r=0

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Slide 55 Use the D3 Javascript Library to Create Interactive Graphs

You can use the D3 javascript library to also create these interactive graphs to make it easier for the user to see percentage breakdowns in a more interactive way. 

http://bl.ocks.org/kerryrodden/7090426

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Slide 56 Mineral Resources On-Line Spatial Data 1

The Minerals Program has just started to create interactive maps but nothing too fancy in ArcGIS.

Currently the Rare Earth Element Deposits are just shown as points on this interactive map, but they could be polygons of the mines if you zoom in far enough to see the details of the region.

This is also an example of how this map requires instructions at the top here since it’s not intuitive to how most people use interactive maps

With Google Maps, we have automatically been trained now to just use a scroll wheel or double click on the map to zoom in and out.

Here you are instructed to use the Shift key and drag the mouse to zoom in.

This map is also an example of how clicking on a point on this map leads to opening another browser window to view the details of the site on this map.

So if I zoom in and click on the nearest location of a Rare Earth Element mine near here in Virginia, it brings you to this window.

http://mrdata.usgs.gov/mineral-resources/ree.html

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Slide 57 Mineral Resources On-Line Spatial Data 2

Suddenly I am completely taken out of the geospatial context and then led down a series of other web pages where I can easily forget and lose the context of where I started in browsing this dataset that already has inherent spatial aspects embedded within it.

http://mrdata.usgs.gov/ree/show-ree.php?rec_id=775 

http://mrdata.usgs.gov/ree/ree.php?mineral=tantalum 

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Slide 58 World Energy Survey Analysis TIBCO Spotfire

Now here is an example of a data visualization tool called Spotfire developed by TIBCO.

First I will start by showing you the tab with the Raw Data, which you should notice is at the end of this series of tabs.

This is what most of the EMEH data looks like in publications.

It really looks quite raw and hard to easily interpret, but the Spotfire interface is intuitively designed to allow you to still access and view the raw data but switch to more visual ways of interpreting the data all within a single interface.

When you click on the different tabs, you are not taken to a completely different web page.

You can also see how the the different graphs interact with each other, allowing you to look at certain types of analysis at a macro and micro scale.

You can easily filter the data in different ways to focus on certain aspects of the data while still seeing other data in context.

http://spotfire.tibco.com/demos/worl...?type=Featured 

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Slide 59 Mobile and Web Apps

This last set of examples is to provide some design ideas related to developing mobile and web applications or even just the user experience for the EM-EH homepage websites.

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Slide 60 Mineral Resource Online Data Catalog 1

Here is the current mobile version of the Mineral Resource Online Data Catalog.

It is a good start to how one might organize content for a small mobile interface, but it also leads you down a series of unknown and confusing paths to how the data is organized.

The key is thinking about a few use cases for how a user would interact with this content on a mobile device and designing the content to fit those particular use cases.

It is also important to design the interface in a way that is familiar to how we are already interacting with mobile applications.

The gestures and design of the content should be familiar and provide visual cues in addition to the text-based categories.

http://mrdata.usgs.gov/catalog/mobile/ 

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Slide 61 Pttrns

This is a website called Pttrns that compiles many common mobile interfaces to give you an idea of the most popular and familiar mobile interface designs currently used.

You can see how color, font size, and images are used to enhance the textual descriptions.

http://dissolve.com/products/001-D461-29-011

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Slide 62 NASA Earth-Now

NASA is quite well known for developing engaging products both on paper and online.

They already have some impressive mobile apps that would be worth trying out to get a better feel for the user experience currently being designed around earth data on a mobile interface.

https://play.google.com/store/apps/d...thnow.activity

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Slide 63 Challenge.gov toxicSlayar

Many agencies are beginning to crowdsource the development of mobile apps for their open data through hackathons.

So instead of designing it in house, they create these challenges like on Challenge.gov and often times the developer makes these apps available for free using the open data from the agency.

Here is an example of a mobile app that uses EPA’s Toxic Release Inventory dataset from 2009 to visualize over 600 chemicals from thousands of US facilities through augmented reality.

This means you can hold your mobile device as if it was in the camera mode (a view of the real world) and then it superimposes the scientific data that is nearby you.

You can also see the Wikipedia pages for each chemical so that a user can quickly learn more about that chemical.

http://challengepost.com/software/toxicslayar 

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Slide 64 Mineral Resource Online Data Catalog 2

One thing you may start to notice on home pages of certain websites is the use of short videos as a background to draw the user in.

It’s a subtle technique but videos ambiently displayed as a background has a subtle affect of drawing a user into your page and make them stay there a little longer.

Here is just a simple example of taking a video clip from a website called Dissolve and showing how it would look to just integrate a video in the background of the Mineral Resources webpage.

http://mrdata.usgs.gov/ 

http://dissolve.com/products/001-D40-16-045

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Slide 65 USGS Toxic Substances Website

I did the same thing with the USGS Toxic Substances website as a way to break up the heavy amount of text on the home page with a video related to toxic contamination. 

Now, I know that putting a video like this as a background on a USGS webpage would not be in compliance with the Visual Identity System Guidance.

But it is worth understanding how subtle design features like videos and moving graphics engages users to want to explore your content.

http://toxics.usgs.gov/about.html 

http://dissolve.com/products/001-D461-29-015 

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Slide 66 Climate Change Impacts in the United States PDF Report

The last example I want to show you is how you can turn a long PDF document that mimics journal publications that many of us scientists are used to and transform this content into interactive webpages.

This is a very long document, literally over 800 pages with lots of text, figures and graphs.

http://s3.amazonaws.com/nca2014/low/...pdf?download=1 

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Slide 67 Climate Change Impacts in the United States Website

But they turned this report into a nicely designed website that breaks up the content and allows readers to interact with the findings in a non-linear format.

http://nca2014.globalchange.gov/

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Slide 68 Pathway Towards Engaging Crowds

So I hope these examples have given you some ideas and insights on how you would like to visualize, present, and communicate your scientific data in new ways.

My goal with each of your projects is to explore how we can engage different crowds to develop similar types of visualizations with your data.

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Slide 69 What is Worth Highlighting

Think about your datasets and what aspects of your data are worth highlighting.

This is just a quick start to an initial breakdown of how we could visualize your data in different ways.

Let me know what are more specific breakdowns that we should consider.

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Slide 70 EMEH Data Formats

Here is also a high level breakdown of the different data formats that you offer in each of the programs and where these datasets are available.

Let me know if there are any others and if there is a certain structure and method for how these datasets are organized on your website and made available to the public.

Web Services
http://mrdata.usgs.gov/wms.html 
http://energy.usgs.gov/Tools/EnergyD...2-web-services

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Slide 71 The Value of a Good API

The main feedback I always hear from users of USGS data is that it is would be better to make the data available through a well-designed API.

Some EM-EH data are available as web services but the key is figuring out how well-designed they are for those using it in practice.

Developing an API helps to standardize your datasets and makes diverse datasets more interoperable.
Developers love APIs because it means they don’t have to download the data just link to it.
APIs also allow users to create web or mobile applications for you.
You can also attract new users to your data more quickly.
But APIs need to have a simple design to facilitate a good developer-friendly experience.
You can also reuse the API for multiple applications and purposes.
The key is designing the API in a way that optimizes for a specific use case.
APIs should also be easy to access and discover.
This allows you to build a community around your API to keep making your API better and relevant to its users.

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Slide 72 EM-EH Challenges & Hackathons

So what I suggest is developing EM-EH Challenges and Hackathons as a way to start targeting interested crowds locally and nationally.

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Slide 73 Crowdsourcing / Geo-Hacking

My initial plan is to begin narrowing my crowdsourcing efforts by asking for volunteers to geo-hack the EMEH data through these Meetup groups, hackathons, and other opportunities.

There are a handful of hackathon Meetups that are local, but there is also the National Day of Civic Hacking on June 6 that will also tap a much larger set of volunteers at a national scale.

I am regularly attending these evening Meetups every week to actively participate in civic hacking myself as well as find venues for promoting the EM-EH projects to interested volunteers.

I also met a high school teacher interested in making these projects available for the Arlington Public School’s Summer Internship program in July, which is a great way to facilitate STEM education in USGS science with high school students.

http://www.meetup.com/Federal-Big-Data-Working-Group/
http://www.meetup.com/DataKind-DC/
http://www.meetup.com/Data-Science-DC/
http://www.meetup.com/Data-Business-DC/
http://www.meetup.com/Geo-DC/ 
http://www.meetup.com/Maptime-DC/
http://hackforchange.org/ 
http://www.apsva.us/domain/2011

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Slide 74 Civic Hacking Goals

The goals for these hacking projects will be threefold.

First, the hackers can produce Proof-of-Concept Visualizations that show different ways to communicate USGS science in a more intuitive way to various types of stakeholders.

Second, the hackers can also provide Examples of How to Tell Better Stories with USGS data to show why and how USGS science is meaningful to our daily lives and relate to broader societal issues.

Third, the hackers can also provide Recommendations on Data Formats and Structures that would allow users to better visualize and interpret these USGS data based on their experience in developing the proof-of-concept visualizations.

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Slide 75 Potential Visualization Tools

There are a plethora of data visualization and geospatial tools beyond just ArcGIS. 

Some of these are free and open source while others may require a subscription service.

But ultimately, I am interested in seeing what different people and crowds come up with given their expertise and the variety of tools that are available to them.

http://opensourcegis.org

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Slide 76 What I Need From You

Now what I need from you is to help me scope these projects specific to your programs. I need your help in drafting challenges for the National Day of Civic Hacking which I can then use to guide the local hackathons as well.

Try to think of challenges that could be done in a weekend as well as something more involved that could be done over a month.

Also think about the different metrics you would want to use to judge each visualization (such as the most engaging, real-world relevance, creative, integrates other datasets).

It also would be helpful to have direct access to some of your experts in your program in case I need to connect the civic hackers and developers to better understand these datasets. 

So think of some domain scientists, GIS specialists, and web developers that you work with in your programs as well as typical and potential users of your data.

This will help me to better understand when I need to do some expert-sourcing and connect certain people with each other when I begin throwing these challenges out to the crowd.

Draft of Challenge: https://docs.google.com/a/doi.gov/do...it?usp=sharing 

Energy: Mark Reidy, Donna Pizzarelli, Mark Engle, Seth Haines
Minerals: Mike Jarvis, Michael Baker
Environmental Health: Daniel Jones

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Slide 77 Positives of Civic Hacking

Hacking has gotten a bad name since it tends to be associated with cybersecurity issues.

Civic hacking is about improving existing processes and systems in creative ways that work effectively with citizens to solve civic problems.

My goal is to show how we can make USGS data more interactive by showing you the evolution the volunteers have made from mockups to proof-of-concepts.

These proof-of-concepts may also show you how we can integrate multiple datasets together that may have never been connected or analyzed together before.

The value of these visualizations is to help you reveal patterns as well as outliers, better decision-making, unexpected insights, data quality and management issues, and possibly predictors of significant trends.

Ultimately I hope you will see the value of civic hackers and possibly the need to hire data scientists, user experience designers, and other types of experts that will be volunteering their time and effort.

https://opengovdata.io/2014/civic-hacking/ 
http://www.codeforamerica.org/blog/2...civic-hacking/ 
http://open.nasa.gov/blog/2013/05/08...-civic-hacker/ 
https://opensource.com/government/14...-civic-hacking 
http://siliconangle.com/blog/2011/03...t-infographic/ 

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Slide 78 Questions?

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USGS Releases Data Management Instructional Memos

USGS has released the long-awaited data management policies, in place currently as "Instructional Memos": 

In addition, the Memos are supported by the USGS Data Management Website: www.usgs.gov/datamanagement
Let me know if you have any questions or comments. 

Thanks, Viv

Viv Hutchison
Science Data Management Branch Chief
US Geological Survey
Core Science Analytics and Synthesis (CSAS)
Denver Federal Center
Building 810, Mail Stop 302
Denver, CO 80225 
303.202.4227 (office)
571.481.7799 (work cell)
vhutchison@usgs.gov

Scientific Data Management Foundation

Source: http://www.usgs.gov/usgs-manual/im/I...I-2015-01.html

U.S. Geological Survey Instructional Memorandum

No: IM OSQI 2015-01

Issuance Date: February 19, 2015

Expiration Date:  Retain Until Suspended

Subject: 
 Scientific Data Management Foundation

1.  Purpose.  This Instructional Memorandum (IM) provides interim policy for establishing a U.S. Geological Survey (USGS) data management foundation following a data lifecycle model.  This interim policy guidance is issued to allow the time needed for USGS science activities to fully implement the data management requirements herein and will be retained until superseded by a permanent Bureau Survey Manual (SM) policy chapter.  Associated IMs related to some elements of the data management lifecycle will be issued separately.

2.  Background.  USGS scientific data encompass a wide variety of information including textual and numeric information, instrument readouts, statistics, images (fixed or moving), diagrams, maps, and audio or video recordings.  They include raw or processed, published, and archived data, for example, data generated by experiments, models, simulations, and by observations of natural phenomena at explicit times and locations and data stored on any type of media. 

3.  Policy.  USGS scientific data shall be managed throughout the data lifecycle as described in section 4 below and, when approved, the data must be released to the public in a machine-readable form under the authority of USGS Fundamental Science Practices (FSP) requirements (SM 502.1).  Guidance and procedures that support this interim policy are available at the USGS Data Management Web site (http://www.usgs.gov/datamanagement).  Other applicable FSP requirements related to review, approval, and release of all USGS science data and information must also be followed (SM 502.2 and SM 502.4).  Refer to IM OSQI-2015-02, IM OSQI-2015-03, and IM OSQI-2015-04 for associated requirements.

4.  Elements of the USGS Science Data Lifecycle Model.  The descriptions of the USGS science data lifecycle elements below represent an overview of results to be achieved.  Refer to the Data Management Web site (http://www.usgs.gov/datamanagement) for more detailed information.

A.  Plan.  The overall project work plan of every research project (SM 502.2) must include planning for data management.  A data management plan describes standards and intended actions for acquiring, processing, analyzing, preserving, publishing/sharing, describing, managing quality, backing up, and securing the data holdings (http://www.usgs.gov/datamanagement/plan.php).  The data management plan, like the work plan, should be updated during the research phase to reflect the reality of the project activities.

B.  Acquire.  Methods and techniques for acquiring research data are planned and documented to ensure that scientific findings are verifiable.  Data acquisition encompasses collecting new data or adding to existing data holdings and may include data purchased or otherwise acquired for use in a USGS data product.  Appropriate methods, agreements, and other requirements for acquiring the data are also considered (http://www.usgs.gov/datamanagement/acquire.php). 

C.  Process.  Data processing denotes those actions or steps performed to verify, organize, transform, repair, integrate, and produce data in an appropriate output form for subsequent use.  Methods of processing are documented to ensure the utility, quality, and integrity of the data (SM 502.2). 

D.  Analyze.  Analysis involves actions and methods performed that help describe facts, detect patterns, develop explanations, and test hypotheses (for example, statistical data analysis, computational modeling, and interpretation of results).  Methods of analysis are documented to ensure the utility and integrity of the data (SM 502.2).

E.  Preserve.  Preservation includes actions and procedures that are performed to ensure that data are retained and accessible consistent with the USGS Records Disposition Schedules and other applicable regulations.  Archiving or transfers to an appropriate data repository or the National Archives and Records Administration are integral aspects of data preservation (http://www.usgs.gov/datamanagement/preserve.php).  Controls are in place to protect proprietary and predecisional data (SM 502.5) and the integrity of the data (refer to Departmental Manual (DM) chapter 305 DM 3).

F.  Publish/Share.  USGS scientific data may be released or disseminated in a variety of ways, for example in datasets and databases, software, and other information products including USGS series publications (SM 1100.3), outside publications (SM 1100.4), and USGS Web pages.  Publishing and sharing of data benefits USGS scientists, the scientific community, the general public, and other stakeholders.  The USGS supports data sharing by providing data services and guidelines such as including the proper citations and use of persistent identifiers (for example, digital object identifiers or DOIs) for data and associated metadata (http://www.usgs.gov/datamanagement/share.php).  All USGS scientific publications must identify their associated datasets.  Refer to SM 502.4 for review, approval, and release requirements for USGS information products.

G.  Describe (Metadata, Documentation).  Metadata describe USGS scientific data and how they were collected and processed, and are essential for reproducibility of research results.  Metadata include specific attributes, such as spatial coverage, scale, collection methods used, citation information, abstract, purpose of the data, and information about how data are formatted.  USGS metadata records follow standards that are endorsed by the Federal Geographic Data Committee (http://www.fgdc.gov), which include metadata standards for both spatial and non-spatial data.  Additional documentation provides information about data in the context of their use in specific systems, applications, and settings, and includes ancillary materials (such as field notes) as a supplement to standardized metadata (http://www.usgs.gov/datamanagement/describe.php).

H.  Manage Quality.  Data management activities (including use of standard methods and best practice techniques) are performed in a consistent, objective, and replicable manner to help ensure that high-quality and verifiable results are achieved (refer to SM 502.2).  Quality assurance checks are performed at all stages of the science data lifecycle (http://www.usgs.gov/datamanagement/qaqc.php). 

I.  Backup and Secure.  During all data management processes, backup copies of data are created to protect against loss that can result from events such as human error, hardware failure, computer viruses, power failure, or natural disaster.  Best practices for backup and securing data at all stages of the data lifecycle are available (http://www.usgs.gov/datamanagement/backup.php). 

5.  Responsibilities.  Everyone in the USGS involved in scientific data-related activities described in section 4 above is responsible for complying with this chapter.  Designated officials have specific roles in establishing the policies and other requirements that underpin data management:

A.  Associate Directors and Regional Directors., Associate Directors (ADs) and Regional Directors (RDs), as members of the USGS Executive Leadership Team (ELT), set policy for how scientific investigations, research, and related activities are carried out and how data and information products are reviewed and approved for release and dissemination.  The ADs and RDs provide oversight and support for the data management processes in their mission and regional areas.  They collaborate with each other to address issues or take corrective action with regard to the data management lifecycle processes. 

B.  Office of Science Quality and Integrity and Core Science Systems.  The Office of Science Quality and Integrity (OSQI) and Core Science Systems (CSS) are responsible for jointly developing USGS data management policy and collaborating on the development of related guidance and procedures.  The OSQI coordinates with the ADs, RDs, or the entire ELT as needed to address and resolve issues regarding the execution of this policy and related data management review and approval processes.  The CSS maintains comprehensive guidance and procedures related to data management (refer to the USGS Data Management Web site).  The OSQI maintains and communicates this and other FSP related policy documents. 

C.  Science Center Directors.  Science Center Directors or their designees ensure compliance with data management requirements for data produced in their centers or offices and consult with their ADs, RDs, Managers (program and project), scientists, and others on their staff as needed with regard to carrying out data management activities, including ensuring the development of data management plans.  They also assign or ensure the assigning of data managers to oversee or steward the lifecycle activities of their respective data products. 

D.  Approving Officials.  Approving Officials, including Science Center Directors (or designees) and Bureau Approving Officials in the OSQI, ensure that USGS standards for scientific quality are followed by confirming that appropriate review, approval, and release requirements are met before they grant Bureau approval of the data products they have authority to approve. 

 

/s/ Alan D. Thornhill                                                                 February 19, 2015

_____________________________________________                  ______________ 
Alan D. Thornhill                                                                                       Date 
Director, Office of Science Quality and Integrity

Metadata for Scientific Data, Software, and Other Information Products

Source: http://www.usgs.gov/usgs-manual/im/I...I-2015-02.html

U.S. Geological Survey Instructional Memorandum

No: IM OSQI 2015-02

Issuance Date: February 19, 2015

Expiration Date:  Retain Until Suspended

Subject: 
  Metadata for Scientific Data, Software, and Other Information Products

1.  Purpose.  This Instructional Memorandum (IM) provides interim policy on metadata requirements for U.S. Geological Survey (USGS) scientific data, software, and other information products.  It also provides guidance for complying with appropriate USGS and other Federal standards, such as the metadata standards endorsed by the Federal Geographic Data Committee (FGDC), the interagency committee that provides metadata guidance for all Federal Government scientific data (geospatial and non-geospatial).  This interim policy is issued to allow the time needed for USGS science activities to fully implement the metadata requirements herein and will be retained until superseded by a permanent Bureau Survey Manual (SM) policy chapter. 

2.  Background.  Clear metadata descriptions answer fundamental questions (who, what, when, where, why, and how) and provide critical information intended to promote scientific collaboration, facilitate discovery, enable effective use, promote accurate interpretation of data, document its nature and quality, and augment the inherent value of USGS data and other products.  Metadata also help users make effective use of scientific USGS data and information and aid the USGS in tracking its data and publications.  Metadata is one of the required lifecycle elements described in IM-OSQI-2015-01 - Scientific Data Management Foundation. 

3.  Policy. 

A.  Metadata must accompany all USGS scientific data, software, and other information products described in this policy that are approved for release.  The content and format of metadata depend upon the type of data, software, or information product being described.  When data, software, and other information products are digitally released, metadata must include an appropriate persistent identifier for the product, such as a digital object identifier or DOI, unless access to the product is restricted.  Metadata records are to be developed in a standardized way that enables users to evaluate the data, software, or information product’s fitness for use in a research context.  Metadata records must be updated to reflect changes and to ensure that links are functioning and continue to point to the intended files.  Machine-readable metadata must be generated to enhance the transfer of information between systems and applications.  Refer to http://www.usgs.gov/datamanagement/describe.php for additional guidance related to metadata.

B.  A minimum of one metadata review by a qualified reviewer is required for all USGS scientific data, software, and other information products approved for release.  A metadata review includes both checking for compliance with metadata standards using a recommended metadata validation tool when available, and performing quality checks.  The metadata review can be conducted as part of the peer review, data review, editorial review, or separately as appropriate.  A report of all metadata reviews (reviewer comments and how they were reconciled) must be included in the package in the internal USGS Information Product Data System (IPDS) that is submitted for Bureau approval. 

4.  Creating Metadata: General Guidelines.

A.  Data.  Metadata must be created for all scientific data, prior to approval and release as a USGS information product (refer to IM-OSQI-2015-03 - Review and Approval of Scientific Data for Release).  This includes geospatial and non-geospatial datasets, databases, and Web data services that are created, collected, or compiled by USGS employees, volunteers, contractors, or data from other sources that are subsequently made part of a USGS dataset, database, or service.  In addition to the records that describe data, metadata records are required to describe databases and Web data services.  The metadata record for these data products is updated throughout the project; for example, metadata should be created at the start of data collection, updated during the course of the project, and updated and reviewed at completion of the project, when the dataset or database may be transferred from the active research environment to a system for long-term preservation.  A metadata record includes information such as who produced the data and why, methodologies and citations, collection and processing methods used, definitions of entities and attributes, geographic location, and any access or use constraints, all of which facilitate evaluation of the data and information.  A metadata record also includes, but is not limited to, authorship, title, abstract and purpose, theme keywords, data quality, temporal extent, and physical location.  Refer to additional guidance on developing metadata for datasets and databases on the Data Management Web site (http://www.usgs.gov/datamanagement/describe.php).  A checklist that provides guidelines to reviewers of metadata for data is available at (http://www.usgs.gov/datamanagement/documents/MetadataReviewChecklist_2014.pdf).

(1) Metadata records for datasets and databases must comply with one of the following FGDC standards: FGDC Content Standard for Digital Geospatial Metadata or the International Organization for Standardization suite of standards (refer to http://www.fgdc.gov/metadata).  Extensions to the standards exist, and those FGDC-approved profiles or extensions that apply must be used.  Similarly, any extensions in the ISO suite of standards that apply must be used.  In the event an official FGDC metadata standard endorsement transition occurs, all new dataset and database metadata records must comply with that new standard. 

(2) Metadata elements must be completed to comply with an applicable current FGDC or ISO standard that is appropriate for the data.  There are both mandatory and optional elements in the standards.  Mandatory elements apply to all data.  Use non-mandatory elements when they apply to the dataset or database to ensure more robust, meaningful, and complete USGS metadata records that increase the ability to understand, use and integrate data.  A persistent identifier, specifically a Digital Object Identifier (DOI) for data obtained from the USGS registration agent, is to be included in the metadata unless access to the data is restricted.  Refer to additional information and about data DOIs for data (http://www.usgs.gov/datamanagement/preserve/persistentIDs.php). 

(3) Metadata need to be shared at particular times in the USGS research process, such as metadata for planned data acquisitions, metadata for fully processed and quality-controlled observations and measurements, and metadata for datasets and databases that are approved for release (refer to IM OSQI-2015-03).  These metadata for approved datasets and databases must be deposited in and shared through the USGS Science Data Catalog (http://data.usgs.gov/datacatalog/).  Creators of this metadata must ensure that records are developed in a format (for example, xml) accepted by clearinghouses or repositories, such as the USGS Science Data Catalog.  The FGDC and the Data Management Websites offer guidance on tools that may be used for creating standardized, well-structured metadata (http://www.fgdc.gov/metadata/geospatial-metadata-tools#availabletools andhttp://www.usgs.gov/datamanagement/describe/metadata.php).

B.  Software.  Metadata for scientific software must be embedded in the software code or associated files accompanying the software and, if the software is published on physical media, included on a label physically attached to the media.  Metadata documentation includes the software descriptive name; a citation reference with author contact information and, as appropriate, reference to a publication(s) that describes the software functionality, purpose, configuration specifications, operating instructions, and intended use; the name/position title and contact information for one or more individuals or organizations responsible for the software or source code to be published; version or revision numbers and dates or another consistent method of describing currency of the software, technical details of the operating environment for the software, including programming languages and supported operating platforms; and available forms of the software, including executable packages and source code.

C.  Other Information Products.  Other information products include, but are not limited to, USGS series publications (SM 1100.3), and outside publications (SM 1100.4).  

(1) Metadata for these products will contain a complete citation with page numbers, volume, and issue if applicable.  For USGS series publications, metadata must include an appropriate persistent identifier to ensure discoverability of the product.  USGS series products must also meet the Library of Congress metadata standards related to citations.

(2) Metadata records for publications must be created using the internal USGS IPDS.  These metadata records include, but are not limited to, authorship, title, originating office or center, product type and number, and reference to any associated data, if applicable.  If other metadata elements apply to the information product, the elements should be included to ensure that metadata records are more complete and useful.  Links to available supporting information such as associated data or software should be included in the metadata unless access to these products is restricted.  Metadata for products approved through the IPDS are deposited in and shared through the USGS Publications Warehouse.  The IPDS Web site also provides internal guidance to USGS employees on developing metadata for these information products. 

5.  Responsibilities.  All USGS employees, contractors, and volunteers engaged in data collection, research, and data development (SM 502.2) activities and in activities related to review, approval, and release of information products (SM 502.4) are responsible for complying with this metadata policy.  Specific responsibilities include:

A.  Associate Directors and Regional Directors.  Associate Directors (ADs) and Regional Directors (RDs) work collaboratively with the entire USGS Executive Leadership Team (ELT), to address issues or take corrective action with regard to metadata policy. 

B.  Office of Science Quality and Integrity and Core Science Systems.  The Office of Science Quality and Integrity (OSQI) and the Core Science Systems (CSS) mission area are responsible for jointly developing USGS metadata policy and collaborating with the ADs and RDs and the entire ELT as needed to resolve issues regarding the implementation of this policy.  They work in coordination with managers and staff in USGS science centers and offices to provide Bureau-wide advice, guidance, and procedures related to metadata for the products specified herein.  The CSS provides metadata related guidance through the Data Management Web site (http://www.usgs.gov/datamanagement/describe.php).  The OSQI maintains and communicates this and other FSP policy documents.

C.  Science Center Directors.  Science Center Directors ensure compliance of the metadata records for the data, software, and other information products that are produced by authors in their centers or offices and consult with their respective ADs and RDs and CSS and OSQI officials and staff as needed in ensuring compliance. 

D.  Approving Officials.  Approving Officials, including Science Center Directors (or their designee) and Bureau Approving Officials in the OSQI, ensure that the appropriate metadata review has occurred and that documentation about the metadata review is included in the package submitted to them for Bureau approval (SM 205.18).

E.  Authors’ Supervisors.  Authors’ Supervisors have the first responsibility in the management chain with regard to ensuring a metadata review occurs.  They consult with their respective Science Center Directors as needed to ensure the quality and adequate maintenance of metadata records for the data, software, and other information products that are produced by authors they supervise. 

F.  Scientists and Authors.  USGS scientists and authors ensure that sufficient metadata records are created for each data, software, and other information product they produce and that these records are consistent, up to date, and verified for accuracy in accordance with the requirements in this policy.  This includes ensuring that the appropriate metadata review, peer review, editorial review, and approval for products they produce are obtained.

 

 

/s/ Alan D. Thornhill                                                                 February 19, 2015

_____________________________________________                  ______________ 
Alan D. Thornhill                                                                                       Date 
Director, Office of Science Quality and Integrity

Review and Approval of Scientific Data for Release 

Source: http://www.usgs.gov/usgs-manual/im/I...I-2015-03.html

U.S. Geological Survey Instructional Memorandum

No: IM OSQI 2015-03

Issuance Date: February 19, 2015

Expiration Date:  Retain Until Suspended

Subject:
 Review and Approval of Scientific Data for Release

1.  Purpose and Scope.  This Instructional Memorandum (IM) provides interim requirements and procedures for review and approval of scientific data prior to release or dissemination.  The IM applies to all U.S. Geological Survey (USGS) scientific data that are released to the public (including, but not limited to, data that are made available in datasets, databases, data services, and publications, as well as model outputs and derived products.  The IM replaces the part of Survey Manual (SM) chapter SM 500.24 - Policy for Release of Computer Databases and Computer Programs, dated April 9, 1993, that addresses Computer Databases.  The part of SM 500.24 that addresses Computer Programs will be addressed separately.  This IM is interim policy to allow the time needed for USGS science activities to fully implement the data release requirements herein and it will be retained until superseded by a permanent Survey Manual (SM) policy chapter.

2.  Background.  Scientific data created by or on behalf of the USGS are the property of the Federal Government.  USGS scientific data are made available publicly and free of restrictions, except in rare cases where access must be restricted because of security, privacy, confidentiality, or other constraints.  It is the policy of the USGS to provide timely public access to scientific data, information, and technologies developed by the Bureau’s information and research programs.  The May 9, 2013, Office of Management and Budget (OMB) memorandum on “Open Data Policy—Managing Data as an Asset,” requires agencies to collect or create information in a way that supports downstream information processing and dissemination activities.  This includes using machine readable and open formats, data standards, and common core and extensible metadata for all new information creation and collection efforts.  The February 22, 2013, Office of Science and Technology Policy (OSTP) memorandum on “Increasing Access to the Results of Federally Funded Scientific Research,” requires public access to digital datasets resulting from federally funded research, including datasets used to support scholarly publications.   

3.  Definitions.  The following definitions pertain to USGS scientific data:

A.  Data.  Observations or measurements (unprocessed or processed) represented as text, numbers, or multimedia. 

B.  Dataset.  A structured collection of data. 

C.  Database.  Datasets and other items stored together to serve one or more purposes or applications, often including data query or search and retrieval capabilities. 

D.  Data Service.  An online capability that allows direct interaction between data and software. 

E.  Provisional Data.  Those data (such as real-time data, preliminary measurements) that are subject to revision, and may be released prior to approval to meet an immediate need (refer to SM 502.5, section 6). 

F.  Approved Data.  Those data that have USGS approval for release pursuant to this chapter and SM 205.18

4.  Policy. 

A.  USGS releases both provisional and approved scientific data.  Until they are approved for release, scientific data are provisional or preliminary and subject to change.  Scientific data described herein, when released, are considered a USGS information product (SM 1100.1) and must comply with the appropriate USGS Fundamental Science Practices (FSP) requirements described herein, as well as in other underlying policy (for example, SM 502.4).

B.  Approved scientific data must comply with the metadata requirements (refer to IM OSQI 2015-02 - Metadata for Scientific Data, Software, and Other Information Products), and the metadata must accompany the data when released.

C.  Reviews of scientific data and associated metadata are required before data are approved (see section 5 below). 

D.  Approved scientific data must be assigned a persistent identifier, specifically a Digital Object Identifier (DOI) from the USGS registration agent, and be accompanied by a recommended citation (refer to http://www.usgs.gov/datamanagement/preserve/persistentIDs.php).

E.  All USGS scientific data must be released with a provisional (preliminary) or approved disclaimer statement.   Where applicable other disclaimer statements such as those regarding non-endorsement of commercial products or use of copyrighted material should be included.  Disclaimers statements to be used are available at the USGS FSP Web site (refer tohttp://www.usgs.gov/fsp/fsp_disclaimers.asp).

F.  Scientific data released by the USGS must be managed and distributed through a data system that can ensure the long-term preservation, discoverability, accessibility, and usability of the resource. 

G.  The procedures and guidance information that support this IM are available at the Data Management Web site (http://www.usgs.gov/datamanagement/).

5.  Review and Approval of Scientific Data.  Scientific data intended for public release are subject to USGS FSP review, approval, and release requirements described below and in SM 502.4 as applicable.  Individual USGS organizational units may establish additional requirements and procedures (refer to SM 502.2). 

A.  A minimum of two reviews are required for approval that include one data review and one metadata review.  These reviews must be documented in the internal USGS Information Product Data System (IPDS).  The metadata review ensures that the requirements of IM OSQI 2015-02 are met.  Unlike peer review (SM 502.3), which establishes the veracity of the scientific interpretation, data review involves checking that the data meet standards for quality and completeness and requires the reviewer to have specialized scientific knowledge of the particular type of data being reviewed (refer to Data Management Web site, http://www.usgs.gov/datamanagement/qaqc.php).  Refer to the data checklist and the metadata checklist for additional guidance on conducting the data and metadata reviews. 

B.  As stated above, scientific data when approved for release are USGS information products.  Scientific data may be approved for release by Science Center Directors or their designees if the data information products contain no new interpretive content and are based on existing published methods.  New interpretive information products, including data that are considered interpretive, must be approved for release by Bureau Approving Officials in the USGS Office of Science Quality and Integrity (SM 205.18).  Examples of interpretive USGS information products, including what qualifies as interpretive data, are available at http://www.usgs.gov/fsp/interpretive_definitions_and_examples.asp.

C.  A peer-reviewed publication documenting collection and processing methods may also be required (SM 502.2).  New interpretive content supporting the creation and/or interpretation of data must be released in a peer reviewed publication such as USGS series or outside publication (i.e., journal articles, cooperator publications, and so on).

6.  Releasing Scientific Data Through Online Databases or Web Services.  When data approved for release and provisional data are released through online databases, Web services and other automated methods of data release, the following apply:

A.  At the online location where the data are released, documentation must be provided to inform the user of the purpose of the service or method, including extent, content, restrictions or terms of use, and instructions for use.  For example, documentation could include methods used to structure and assemble the data and use the Application Programming Interfaces (APIs).  The documentation and procedures are reviewed as part of the approval process for the database or online service. 

B.  Maintenance and oversight of the online database, Web service, or automated method will be performed under the direction of an assigned manager who oversees the process that ensures the quality of data added to the database or service, routine data reviews, and documentation of methods and procedures. 

7.  Responsibilities.  All those involved in any phase of the scientific data release process, including data producers, managers, and reviewers, are responsible for complying with this policy.  In addition, specific responsibilities include:

A.  Associate Directors and Regional Directors.  Associate Directors (ADs) and Regional Directors (RDs) coordinate with Science Center Directors to ensure appropriate stewardship of the data produced in their respective mission and regional areas. 

B.  Office of Science Quality and Integrity and Core Science Systems.  The Office of Science Quality and Integrity (OSQI) and Core Science Systems (CSS) are responsible for jointly developing USGS data release policy and collaborating on the development of related guidance and procedures.  The OSQI and CSS coordinate with the ADs, RDs and other USGS mission area and office staff to provide advice, procedures, and guidance regarding processes for data review, approval, and release.  The OSQI is responsible for communicating and maintaining the policy documents related to scientific data release.  The CSS is responsible for maintaining data release related guidance found on the Data Management Website (http://www.usgs.gov/datamanagement/share.php).

C.  Science Center Directors, Managers, Supervisors, and Authors.  Science Center Directors, managers (i.e., project and program), supervisors, and authors of data consult and work with each other, OSQI and CSS managers, and approving officials, as needed during the processes of review, approval, and release of scientific data.  Science Center Directors and managers collaborate with their mission area ADs and RDs as necessary to assign or ensure the assigning or designating of data managers to steward the scientific data produced in their respective offices and centers.

D.  Data Managers.  Data managers, as the assigned or designated individuals, teams, or organizations are responsible for stewarding scientific data through the release process.  They collaborate with their mission area Science Center Directors, managers, supervisors, and scientists in the conduct of their data stewardship activities. 

E.  Approving Officials.  Approving officials, including Science Center Directors (or their designees) and Bureau Approving Officials in the OSQI, collaborate with authors, mission area managers, and others as needed regarding review and approval of scientific data.  They have latitude in determining what is needed to uphold USGS standards for data quality, including ensuring the necessary reviews are obtained and the method of release is appropriate.

 

 

/s/ Alan D. Thornhill                                                                 February 19, 2015

_____________________________________________                  ______________ 
Alan D. Thornhill                                                                                       Date 
Director, Office of Science Quality and Integrity

Preservation Requirements for Digital Scientific Data 

Source: http://www.usgs.gov/usgs-manual/im/I...I-2015-04.html

U.S. Geological Survey Instructional Memorandum

No: IM OSQI 2015-04

Issuance Date: February 19, 2015

Expiration Date:  Retain Until Suspended

Subject:
 Preservation Requirements for Digital Scientific Data

1.  Purpose and Scope.  This Instructional Memorandum (IM) specifies preservation requirements that apply to all U.S. Geological Survey (USGS) digital scientific data and associated information.  The IM is interim policy to allow the time needed for USGS science activities to fully implement the data preservation requirements herein and it will be retained until superseded by a permanent Bureau Survey Manual (SM) policy chapter.  This Instructional Memorandum (IM) provides interim requirements and procedures to ensure the preservation of USGS digital scientific data.  Preservation requirements for non-digital data (paper records containing data or descriptions of data) or physical samples are addressed in the USGS records disposition schedules.

2.  Policy.  Data created by or on behalf of the USGS are the property of the Federal Government (refer to SM 502.5 for information on USGS and non USGS data) and the Federal Records Act 36 CFR 1220.14 ).  It is the policy of the USGS to preserve scientific data and information funded or developed by the Bureau’s information and research programs.  All scientific data as a result of USGS funding must be preserved as follows. 

A.  USGS scientific data, databases and information, are accessible, available, and useable on the appropriate media in accordance with the USGS records disposition schedules (http://www.usgs.gov/usgs-manual/schedule/) or as appropriate to meet the National Archives and Records Administration (NARA) retention format requirements for permanent records (http://www.archives.gov/records-mgmt/policy/transfer-guidance-tables.html#digitalstillimages) and to comply with Federal Government Open Data and Open Access initiatives. 

B.  The USGS will retain an authoritative or original copy of all data for which it is responsible and that are produced for release as a result of its scientific research and related activities.  Distribution copies of USGS data may be disseminated through appropriate third parties such as, journal-related storage and external repository.  When scientific data are produced in cooperation with non-USGS entities, ownership of that data must be clearly stated in a documented agreement between the parties.  In addition, other applicable requirements for scientific work performed and information developed under various agreements or collaborative arrangements with non-USGS entities must also be followed (refer to SM 502.2, section 2.  References).

C.  Digital data and associated information that USGS is responsible for preserving must be stored and released from properly certified and accredited information systems following USGS information technology systems processes and procedures.  These processes ensure important long-term preservation concerns such as those related to fault tolerance, data integrity, and information security are addressed (refer to http://www.usgs.gov/usgs-manual/600/600-5.html).

3.  Preservation Elements.  Each element listed below represents a component of required digital scientific data preservation.  Detailed guidance and specific implementation details are available on the USGS Data Management Web site: http://www.usgs.gov/datamanagement/preserve.php.

A.  Storage and Geographic Location.  Storage and geographic location involves storage systems, locations, and the planning for multiple copies of data.  At a minimum, two complete copies of all data, metadata, and documentation must be maintained.  These two copies must be geographically separate; for example, a backup tape/disk can be stored in a location that is separate from a Science Center, which is the primary location of the data/metadata.

B.  Data Viability and Integrity.  Data viability and integrity encompass procedures to maintain the ability to access and use data through time.  This includes activities to prevent, detect, and recover from unexpected, deliberate or intentional, or unintentional changes to data as well as activities that maintain the viability of data through technological or other changes over time.  Examples include verifying file integrity at fixed intervals, maintaining procedures to replace or repair corrupted data, migration of data, transferring at-risk data to newer computer hardware from degrading or obsolete media, and upgrading operating systems and media.

C.  Information Security.  Information security includes procedures to prevent human-caused corruption or deletion of and unauthorized access to the data.  Role-based authorization applies with regard to read, write, move, and delete actions on individual files. 

D.  Metadata.  Metadata ensures proper documentation of Bureau data to enable contextual understanding and long-term usability (refer to IM OSQI 2015-02 - Metadata for Scientific Data, Software, and Other Information Products).  Complete metadata must be preserved and directly associated with the scientific data they describe. 

E.  File Formats.  The file formats include file types, data structures, and naming conventions to aid long-term preservation, access, and use.  The USGS must comply with NARA formats for records deemed to be permanent (refer to http://www.archives.gov/records-mgmt/policy/transfer-guidance-tables.html).   The USGS encourages the use of open file formats, codecs, compression schemes, and encapsulation schemes.  These formats shall meet the Office of Management and Budget principles of ensuring machine readability.  Nonproprietary, open data formats are preferred over proprietary formats requiring specialized software for access and use.

4.  Responsibilities. 

A.  Associate Directors and Regional Directors.  Associate Directors (ADs) and Regional Directors (RDs) provide oversight and support for the data preservation activities in their mission and regional areas.  They collaborate with each other to address issues or take corrective action with regard to data preservation activities.

B.  Office of Science Quality and Integrity and Core Science Systems.  The Office of Science Quality and Integrity (OSQI) and the Core Science Systems (CSS) are responsible for jointly developing data preservation policy.  The OSQI is responsible for maintaining and communicating policy regarding the preservation of USGS digital scientific data assets.  The CSS maintains the USGS Data Management Web site, which provides guidance and procedures related to preservation of scientific data (refer to http://www.usgs.gov/datamanagement/preserve.php) and the USGS Science Data Catalog, which provides public search and discovery of USGS digital scientific data. 

C.  Science Center Directors, Managers, and Scientists.  Science Center Directors, managers (project and program), and scientists involved in any phase of the USGS science data lifecycle (refer to IM OSQI 2015-01 - Scientific Data Management Foundation), are responsible for complying with the preservation requirements in this policy.  Science Center Directors or their designees as they deem necessary, collaborate with their respective ADs and/or RDs to assign or ensure the assigning of data managers to oversee their centers’ and offices’ data preservation activities.  At the start of the project, the scientist must develop a data migration strategy as part of the data management plan to account for preserving the data and information and the metadata in accordance with this policy and records disposition authorities.

D.  Data Managers.  Designated data managers are responsible for coordinating and enacting preservation activities for USGS data.  Data managers will ensure that the preservation activities for which they are assigned are met.  They also collaborate with the data producers and the USGS Records Officer to ensure the appropriate records management requirements for their data are met. 

E.  Records Officer.  The USGS Records Officer in the Office of Enterprise Information is responsible for the policy development, coordination, and overall management of the USGS Records Management Program and ensuring policies, standards, and procedures are in place that provide guidance on creating accurate and complete records, maintaining these records throughout the science data lifecycle, and legally transferring permanent scientific data in accordance with applicable USGS and NARA records management requirements.

 

 

/s/ Alan D. Thornhill                                                                 February 19, 2015

_____________________________________________                  ______________ 
Alan D. Thornhill                                                                                       Date 
Director, Office of Science Quality and Integrity

Mineral Commodity Summaries 2015

Source: http://minerals.usgs.gov/minerals/pu...15/mcs2015.pdf (PDF)

Cover Page

MineralCommoditySummaries2015CoverPage.png

Inside Cover Page

U.S. Department of the Interior
SALLY JEWELL, Secretary

U.S. Geological Survey
Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

Manuscript approved for publication January 30, 2015.

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment—visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprod

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Mail: Stop IDCC; Washington, DC 20402–0001
Phone: (866) 512–1800 (toll-free); (202) 512–1800 (DC area)
Fax: (202) 512–2104
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Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted material contained within this report.

Suggested citation:
U.S. Geological Survey, 2015, Mineral commodity summaries 2015: U.S. Geological Survey, 196 p., http://dx.doi.org/10.3133/70140094.

ISBN 978–1–4113–3877–7

Other Information

INSTANT INFORMATION

Information about the U.S. Geological Survey, its programs, staff, and products is available from the Internet at <http://www.usgs.gov> or by calling (888) ASK–USGS [(888) 275–8747].
This publication has been prepared by the National Minerals Information Center. Information about the Center and its products is available from the Internet at <http://minerals.usgs.gov/minerals> or by writing to Director, National Minerals Information Center, 988 National Center, Reston, VA 20192.

KEY PUBLICATIONS

Minerals Yearbook—These annual publications review the mineral industries of the United States and of more than 180 other countries. They contain statistical data on minerals and materials and include information on economic and technical trends and developments. The three volumes that make up the Minerals Yearbook are Volume I, Metals and Minerals; Volume II, Area Reports, Domestic; and Volume III, Area Reports, International.

Mineral Commodity Summaries—Published on an annual basis, this report is the earliest Government publication to furnish estimates covering nonfuel mineral industry data. Data sheets contain information on the domestic industry structure, Government programs, tariffs, and 5-year salient statistics for more than 90 individual minerals and materials.

Mineral Industry Surveys—These periodic statistical and economic reports are designed to provide timely statistical data on production, distribution, stocks, and consumption of significant mineral commodities. The surveys are issued monthly, quarterly, or at other regular intervals.

Metal Industry Indicators—This monthly publication analyzes and forecasts the economic health of three metal industries (primary metals, steel, and copper) using leading and coincident indexes.

Nonmetallic Mineral Products Industry Indexes—This monthly publication analyzes the leading and coincident
indexes for the nonmetallic mineral products industry (NAICS 327).

Materials Flow Studies—These publications describe the flow of materials from source to ultimate disposition to help better understand the economy, manage the use of natural resources, and protect the environment.

Recycling Reports—These materials flow studies illustrate the recycling of metal commodities and identify recycling trends.

Historical Statistics for Mineral and Material Commodities in the United States (Data Series 140)—This report provides a compilation of statistics on production, trade, and use of approximately 90 mineral commodities since as far back as 1900.

WHERE TO OBTAIN PUBLICATIONS

  • Mineral Commodity Summaries and the Minerals Yearbook are sold by the U.S. Government Printing Office.
  • Orders are accepted over the Internet at <http://bookstore.gpo.gov>, by telephone toll free (866) 512–1800; Washington, DC area (202) 512–1800, by fax (202) 512–2104, or through the mail (P.O. Box 979050, St. Louis, MO 63197–9000).
  • All current and many past publications are available in PDF format (and some are available in XLS format) through <http://minerals.usgs.gov/minerals>.

General

Introduction

Each chapter of the 2015 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2014 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses.

For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.

Abbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. “Appendix C—Reserves and Resources” includes “Part A—Resource/Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is Appendix D.

The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2015 are welcomed.

Growth Rates of Leading and Coincident Indexes for Mineral Products

The leading indexes historically give signals several months in advance of major changes in the corresponding coincident index, which measures current industry activity. The growth rates, which can be viewed as trends, are expressed as compound annual rates based on the ratio of the current month's index to its average level during the preceding 12 months.

Sources: U.S. Geological Survey, Metal Industry Indicators and Nonmetallic Mineral Products Industry Indexes.

MineralCommoditySummarie2015Figure1.png

The Role of Nonfuel Minerals in the U.S. Economy

1 Major consuming industries of processed mineral materials are construction, durable goods manufacturers, and some nondurable goods manufacturers. The value of shipments for processed mineral materials cannot be directly related to gross domestic product.

Sources: U.S. Geological Survey and the U.S. Department of Commerce

MineralCommoditySummarie2015Figure2.png

2014 U.S. Net Import Reliance for Selected Nonfuel Mineral Materials

1 Not all mineral commodities covered in this publication are listed here. Those not shown include mineral commodities for which the United States is a net exporter (for example, molybdenum) or less than 5% import reliant (for example, lime). For some mineral commodities (for example, hafnium), not enough information is available to calculate the exact percentage of import reliance; for others (for example, tellurium), exact percentages may have been rounded to avoid disclosing company proprietary data.

2 In descending order of import share.

3 Data include lanthanides and yttrium but exclude most scandium.

MineralCommoditySummarie2015Figure3.png

Significant Events, Trends, and Issues

In 2014, the estimated value of total nonfuel mineral production increased in the United States. The quantity of production increased for most mineral commodities mined in the United States. Prices increased for the majority of mineral commodities, but notable exceptions were the declines in prices for most precious metals. Minerals remained fundamental to the U.S. economy, contributing to the real gross domestic product (GDP) at several levels, including mining, processing, and manufacturing finished products. Following the reduction in construction activity that began with the 2008–09 recession and continued through 2011, the construction industry continued to expand in 2014, with increased production and consumption of cement, construction sand and gravel, crushed stone, and gypsum, mineral commodities that are used almost exclusively in construction.

The figure on page 4 shows that the primary metals industry and the nonmetallic minerals products industry are fundamentally cyclical. Growth rates are directly affected by the U.S. business cycle as well as by global economic conditions. The U.S. Geological Survey (USGS) generates composite indexes to measure economic activity in these industries. The coincident composite indexes describe the current situation using production, employment, and shipments data. The leading composite indexes signal major changes in the industry’s direction by such variables as stock prices, commodity prices, new product orders, and other indicators, which are combined into one gauge. For each of the indexes, a growth rate is calculated to measure its change relative to the previous 12 months. The primary metals leading index growth rate started slowly in 2014, mainly because of the effect that severe weather had on U.S. business activity. It accelerated through mid-year; however, it turned down and settled in negative territory by yearend. U.S. economic growth supported the domestic primary metals industry; however, weak global economic growth and the strong U.S. dollar limited U.S. exports. Meanwhile, low-priced metal imports increased during most of 2014. Metals consumption in the manufacturing sector increased during the year; however, decreased new orders for durable goods in the latter part of the year will likely reduce metals demand in this sector in 2015. A rise in nonresidential construction projects also increased metals demand in 2014. One of the largest nonresidential construction activities in 2014 was manufacturing plant building. The nonmetallic mineral products industry also benefitted from this increase in construction spending in 2014. This offset some of the slower growth in the residential construction industry in 2014. However, in 2015, residential construction indicators, such as housing starts and building permits, point to increases in single-family home building, which is the largest portion of residential construction activity. The nonmetallic mineral products leading index growth rate ended 2014 indicating slow growth in the nonmetallic mineral products industry in 2015.

Figure 1 Major Metal-Producing Areas

MineralCommoditySummarie2015Figure4.png

As shown in the figure on page 5, the estimated value of mineral raw materials produced at mines in the United States in 2014 was $77.6 billion, a 3.5% increase from $75.0 billion in 2013. Net exports of mineral raw materials and old scrap contributed an additional $15.0 billion to the U.S. economy. Domestic raw materials and domestically recycled materials were used to process mineral materials worth $697 billion. These mineral materials, including aluminum, brick, copper, fertilizers, and steel, and net imports of processed materials (worth about $41 billion) were, in turn, consumed by downstream industries with a value added of an estimated $2.53 trillion in 2014.

Figure 2 Major Industrial Mineral-Producing Areas Part I

MineralCommoditySummarie2015Figure5.png

The estimated value of U.S. metal mine production in 2014 was $31.5 billion (table 1), slightly less than that of 2013. Principal contributors to the total value of metal mine production in 2014 were copper (32%), gold (27%), iron ore (16%), molybdenum (10%), and zinc (6%). Changes in average prices for domestically mined metals were mixed in 2014. After increased yearly average prices from 2002–12, gold prices decreased for the second consecutive year. The estimated value of U.S. industrial minerals mine production in 2014 was $46.1 billion, about 7% more than that of 2013. The value of industrial minerals mine production in 2013 was dominated by crushed stone (28%), cement (17%), and construction sand and gravel (15%). In general, industrial minerals prices increased slightly.

Table 1 U.S. Mineral Industry Trends
Year 2010 2011 2012 2013 2014e
Total mine production (million dollars):          
Metals 30,300 36,000 34,700 32,100 31,500
Industrial minerals 36,200 38,800 40,900 42,900 46,100
Coal 38,600 44,900 40,600 36,600 37,700
Employment (thousands of production workers):          
Coal mining 70 78 74 68 67
Metal mining 29 1 98 1 101 1 100 1 100
Industrial minerals, except fuels 71 2 NA 2 NA 2 NA 2 NA
Chemicals and allied products 474 480 491 490 497
Stone, clay, and glass products 283 278 273 275 283
Primary metal industries 275 301 317 306 312
Average weekly earnings of production workers (dollars):          
Coal mining 1,365 1,404 1,348 1,361 1,440
Chemicals and allied products 888 911 910 919 918
Stone, clay, and glass products 727 767 766 782 827
Primary metal industries 880 889 907 960 989

e Estimated. NA Not available.
1 Metal mining and industrial minerals (except fuel), combined.
2 Because of changes to U.S. Department of Labor reports, these data are no longer available.
Sources: U.S. Geological Survey, U.S. Department of Energy, U.S. Department of Labor.

Table 2 U.S. Mineral-Related Economic Trends
Year 2010 2011 2012 2013 2014e
Gross domestic product (billion dollars) 14,964 15,518 16,163 16,768 17,393
Industrial production (2007=100):          
Total index 91 94 97 100 104
Manufacturing 87 90 94 96 100
Nonmetallic mineral products 69 70 71 74 78
Primary metals: 91 97 100 101 106
Iron and steel 89 98 101 100 103
Aluminum 92 98 103 103 106
Nonferrous metals (except aluminum) 112 114 112 120 129
Chemicals 86 86 86 88 90
Mining: 101 107 114 119 130
Coal 94 95 88 86 85
Oil and gas extraction 110 115 127 137 154
Metals 96 98 99 99 100
Nonmetallic minerals 73 75 76 78 83
Capacity utilization (percent):          
Total industry: 74 76 77 78 79
Mining: 84 86 87 87 89
Metals 74 74 72 72 75
Nonmetallic minerals 70 75 78 82 86
Housing starts (thousands) 586 612 784 930 1,004
Light vehicle sales (thousands) 1 8,620 9,760 11,200 12,200 13,200
Highway construction, value, put in place (billion dollars) 82 80 80 81 83

e Estimated.
1 Excludes imports.
Sources: U.S. Department of Commerce, Federal Reserve Board, Autodata Corp., and U.S. Department of Transportation

Mine production of 14 mineral commodities was worth more than $1 billion each in the United States in 2014. These were, in decreasing order of value, crushed stone, copper, gold, cement, construction sand and gravel, iron ore (shipped), industrial sand and gravel, molybdenum concentrates, phosphate rock, lime, salt, zinc, soda ash, and clays (all types).

The figure on page 6 illustrates the reliance of the United States on foreign sources for raw and processed mineral materials. In 2014, the supply for more than one-half of U.S. apparent consumption of 43 mineral commodities shown in the figure came from imports, and the United States was 100% import reliant for 19 of those. U.S. import reliance has increased significantly since 1978, the year that this information was first reported. At that time, the United States was 100% import reliant for 7 mineral commodities, and more than 50% import reliant for 25 mineral commodities. In 2014, the United States was a net exporter of 17 mineral commodities, meaning more of those domestically produced mineral commodities were exported than imported. That figure has remained relatively stable, with net exports of 18 mineral commodities in 1978.

Figure 3 Major Industrial Mineral-Producing Areas Part II

MineralCommoditySummarie2015Figure6.png

In 2014, 12 States each produced more than $2 billion worth of nonfuel mineral commodities. These States were, in descending order of value—Arizona, Nevada, Minnesota, Texas, Utah, California, Alaska, Florida, Missouri, Michigan, Wyoming, and Colorado. The mineral production of these States accounted for 62% of the U.S. total output value (table 3)

Table 3 Value of Nonfuel Mineral Production in the United States and Principal Nonfuel Minerals Produced in 2014 p, 1
State Value (thousands $) Rank Percent of U.S. total Principal minerals, in order of value
Alabama 1,080,000 24 1.39 Cement (portland), stone (crushed), lime, sand and gravel (construction), cement (masonry).
Alaska 3,510,000 7 4.52 Zinc, gold, lead, silver, sand and gravel (construction).
Arizona 8,060,000 1 10.38 Copper, molybdenum concentrates, sand and gravel (construction), cement (portland), stone (crushed).
Arkansas 1,030,000 26 1.33 Cement (portland), stone (crushed), bromine, sand and gravel (industrial), sand and gravel (construction).
California 3,510,000 6 4.53 Sand and gravel (construction), cement (portland), boron minerals, stone (crushed), gold.
Colorado 2,320,000 12 2.99 Molybdenum concentrates, sand and gravel (construction), cement (portland), gold, stone (crushed).
Connecticut 2 202,000 43 0.26 Stone (crushed), sand and gravel (construction), clays (common), gemstones (natural).
Delaware 2 14,400 50 0.02 Sand and gravel (construction), magnesium compounds, stone (crushed), gemstones (natural).
Florida 2,990,000 8 3.86 Phosphate rock, stone (crushed), cement (portland), sand and gravel (construction), cement (masonry).
Georgia 1,600,000 15 2.06 Clays (kaolin), stone (crushed), cement (portland), clays (fuller's earth), sand and gravel (construction).
Hawaii 107,000 47 0.14 Stone (crushed), sand and gravel (construction), gemstones (natural).
Idaho 1,200,000 21 1.55 Molybdenum concentrates, phosphate rock, sand and gravel (construction), silver, lead.
Illinois 1,460,000 17 1.88 Sand and gravel (industrial), stone (crushed), sand and gravel (construction), cement (portland), tripoli.
Indiana 818,000 30 1.05 Stone (crushed), cement (portland), lime, sand and gravel (construction), cement (masonry).
Iowa 757,000 31 0.98 Stone (crushed), cement (portland), sand and gravel (industrial), sand and gravel (construction), lime.
Kansas 1,030,000 27 1.33 Helium (Grade–A), cement (portland), salt, stone (crushed), helium (crude).
Kentucky 857,000 29 1.10 Stone (crushed), lime, cement (portland), sand and gravel (construction), sand and gravel (industrial).
Louisiana 2 554,000 34 0.71 Salt, sand and gravel (construction), stone (crushed), sand and gravel (industrial), lime.
Maine 2 95,000 48 0.12 Sand and gravel (construction), cement (portland), stone (crushed), stone (dimension), cement (masonry).
Maryland 2 277,000 41 0.36 Cement (portland), stone (crushed), sand and gravel (construction), cement (masonry), stone (dimension).
Massachusetts 2 293,000 39 0.38 Stone (crushed), sand and gravel (construction), stone (dimension), lime, clays (common).
Michigan 2,410,000 10 3.11 Iron ore (usable shipped), cement (portland), sand and gravel (construction), stone (crushed), salt.
Minnesota 2 4,710,000 3 6.07 Iron ore (usable shipped), sand and gravel (industrial), sand and gravel (construction), stone (crushed), stone (dimension).
Mississippi 192,000 44 0.25 Sand and gravel (construction), stone (crushed), clays (fuller's earth), clays (ball), clays (bentonite).
Missouri 2,480,000 9 3.19 Cement (portland), stone (crushed), lead, lime, sand and gravel (industrial).
Montana 1,320,000 19 1.70 Palladium metal, copper, molybdenum concentrates, platinum metal, gold
Nebraska 326,000 37 0.42 Cement (portland), stone (crushed), sand and gravel (construction), sand and gravel (industrial), lime.
Nevada 7,490,000 2 9.66 Gold, copper, silver, lime, diatomite.
New Hampshire 111,000 46 0.14 Sand and gravel (construction), stone (crushed), stone (dimension), gemstones (natural).
New Jersey 2 288,000 40 0.37 Stone (crushed), sand and gravel (construction), sand and gravel (industrial), greensand marl, peat.
New Mexico 1,870,000 13 2.40 Copper, potash, sand and gravel (construction), molybdenum concentrates, stone (crushed).
New York 1,370,000 18 1.76 Salt, stone (crushed), sand and gravel (construction), cement (portland), wollastonite.
North Carolina 1,290,000 20 1.66 Stone (crushed), phosphate rock, sand and gravel (construction), sand and gravel (industrial), clays (common).
North Dakota 2 232,000 42 0.30 Sand and gravel (construction), lime, stone (crushed), clays (common), sand and gravel (industrial).
Ohio 2 1,150,000 22 1.48 Stone (crushed), salt, sand and gravel (construction), lime, cement (portland).
Oklahoma 734,000 32 0.94 Stone (crushed), cement (portland), sand and gravel (industrial), sand and gravel (construction), helium (Grade–A).
Oregon 357,000 36 0.46 Stone (crushed), sand and gravel (construction), cement (portland), diatomite, perlite (crude).
Pennsylvania 2 1,560,000 16 2.01 Stone (crushed), cement (portland), lime, sand and gravel (construction), sand and gravel (industrial).
Rhode Island 2 69,200 49 0.09 Sand and gravel (construction), stone (crushed), sand and gravel (industrial), gemstones (natural).
South Carolina 2 581,000 33 0.75 Cement (portland), stone (crushed), sand and gravel (construction), sand and gravel (industrial), cement (masonry).
South Dakota 311,000 38 0.40 Gold, cement (portland), stone (crushed), sand and gravel (construction), lime.
Tennessee 1,070,000 25 1.38 Stone (crushed), zinc, cement (portland), sand and gravel (construction), sand and gravel (industrial).
Texas 4,240,000 4 5.39 Stone (crushed), cement (portland), sand and gravel (construction), sand and gravel (industrial), salt.
Utah 4,180,000 5 5.38 Copper, gold, molybdenum concentrates, magnesium metal, potash.
Vermont 2 128,000 45 0.16 Stone (crushed), sand and gravel (construction), stone (dimension), talc (crude), gemstones (natural).
Virginia 1,110,000 23 1.43 Stone (crushed), cement (portland), lime, sand and gravel (construction), sand and gravel (industrial).
Washington 890,000 28 1.15 Sand and gravel (construction), stone (crushed), gold, cement (portland), diatomite.
West Virginia 371,000 35 0.48 Stone (crushed), cement (portland), lime, sand and gravel (industrial), cement (masonry).
Wisconsin 2 1,780,000 14 2.29 Sand and gravel (industrial), sand and gravel (construction), stone (crushed), lime, stone (dimension).
Wyoming 2,350,000 11 3.03 Soda ash, helium (Grade–A), clays (bentonite), sand and gravel(construction), cement (portland).
Undistributed 871,000 XX 1.12  
Total 77,600,000 XX 100.00  

p Preliminary. XX Not applicable.
1 Data are rounded to no more than three significant digits; may not add to totals shown.
2 Partial total; excludes values that must be concealed to avoid disclosing company proprietary data. Concealed values included with “Undistributed.”

The Defense Logistics Agency (DLA) Strategic Materials is responsible for providing safe, secure, and environmentally sound stewardship for strategic and critical materials in the U.S. National Defense Stockpile (NDS). DLA Strategic Materials stores 27 commodities at 9 locations in the United States. In fiscal year 2014, DLA Strategic Materials sold $68 million of excess mineral materials from the NDS. At the end of the fiscal year, mineral materials valued at $1.5 billion remained in the NDS. Of the remaining material, some was being held in reserve, some was offered for sale, and sales of some of the materials were suspended. Additional detailed information can be found in the “Government Stockpile” sections in the mineral commodity chapters that follow. Under the authority of the Defense Production Act of 1950, the U.S. Geological Survey advises the DLA on acquisition and disposals of NDS mineral materials.

Appendix A—Abbreviations and Units of Measure

Abbreviations and Units of Measure

1 carat (metric) (diamond) = 200 milligrams
1 flask (fl) = 76 pounds, avoirdupois
1 karat (gold) = one twenty-fourth part
1 kilogram (kg) = 2.2046 pounds, avoirdupois
1 long ton (lt) = 2,240 pounds, avoirdupois
1 long ton unit (ltu) = 1% of 1 long ton or 22.4 pounds avoirdupois
long calcined ton (lct) = excludes water of hydration
long dry ton (ldt) = excludes excess free moisture
Mcf = 1,000 cubic feet
1 metric ton (t) = 2,204.6 pounds, avoirdupois or 1,000 kilograms
1 metric ton (t) = 1.1023 short ton
1 metric ton unit (mtu) = 1% of 1 metric ton or 10 kilograms
metric dry ton (mdt) = excludes excess free moisture
1 pound (lb) = 453.6 grams
1 short ton (st) = 2,000 pounds, avoirdupois
1 short ton unit (stu) = 1% of 1 short ton or 20 pounds, avoirdupois
short dry ton (sdt) = excludes excess free moisture
1 troy ounce (tr oz) = 1.09714 avoirdupois ounces or 31.103 grams
1 troy pound = 12 troy ounces

Appendix B—Definitions of Selected Terms Used in This Report

Terms Used for Materials in the National Defense Stockpile and Helium Stockpile

Inventory refers to the quantity of mineral materials held in the National Defense Stockpile or in the Federal Helium Reserve. Nonstockpile-grade materials may be included in the table; where significant, the quantities of these stockpiled materials will be specified in the text accompanying the table.

Authorized for disposal refers to quantities that are in excess of the stockpile goal for a material, and for which Congress has authorized disposal over the long term at rates designed to maximize revenue but avoid undue disruption to the usual markets and financial loss to the United States.

Disposal plan FY 2014 indicates the total amount of a material in the National Defense Stockpile that the U.S. Department of Defense is permitted to sell under the Annual Materials Plan approved by Congress for the fiscal year. FY 2014 (fiscal year 2014 is the period October 1, 2013, through September 30, 2014). For mineral commodities that have a disposal plan greater than the inventory, actual quantity will be limited to remaining disposal authority or inventory. Note that, unlike the National Defense Stockpile, helium stockpile sales by the Bureau of Land Management under the Helium Privatization Act of 1996 are permitted to exceed disposal plans.

Disposals FY 2014 refers to material sold or traded from the stockpile in FY 2014.

Depletion Allowance

The depletion allowance is a business tax deduction analogous to depreciation, but which applies to an ore reserve rather than equipment or production facilities. Federal tax law allows this deduction from taxable corporate income, recognizing that an ore deposit is a depletable asset that must eventually be replaced.

Appendix C—Reserves and Resources

Reserves data are dynamic. They may be reduced as ore is mined and/or the extraction feasibility diminishes, or more commonly, they may continue to increase as additional deposits (known or recently discovered) are developed, or currently exploited deposits are more thoroughly explored and/or new technology or economic variables improve their economic feasibility. Reserves may be considered a working inventory of mining companies’ supply of an economically extractable mineral commodity. As such, the magnitude of that inventory is necessarily limited by many considerations, including cost of drilling, taxes, price of the mineral commodity being mined, and the demand for it. Reserves will be developed to the point of business needs and geologic limitations of economic ore grade and tonnage. For example, in 1970, identified and undiscovered world copper resources were estimated to contain 1.6 billion metric tons of copper, with reserves of about 280 million metric tons of copper. Since then, almost 480 million metric tons of copper have been produced worldwide, but world copper reserves in 2014 were estimated to be 700 million metric tons of copper, more than double those in 1970, despite the depletion by mining of more than the original estimated reserves.

Future supplies of minerals will come from reserves and other identified resources, currently undiscovered resources in deposits that will be discovered in the future, and material that will be recycled from current inuse stocks of minerals or from minerals in waste disposal sites. Undiscovered deposits of minerals constitute an important consideration in assessing future supplies. USGS reports provide estimates of undiscovered mineral resources using a three-part assessment methodology (Singer and Menzie, 2010). Mineral-resource assessments have been carried out for small parcels of land being evaluated for land reclassification, for the Nation, and for the world.

Reference Cited

Singer, D.A., and Menzie, W.D., 2010, Quantitative mineral resource assessments—An integrated approach: Oxford, United Kingdom, Oxford University Press, 219 p.

Part A—Resource/Reserve Classification for Minerals1
Introduction

Through the years, geologists, mining engineers, and others operating in the minerals field have used various terms to describe and classify mineral resources, which as defined herein include energy materials. Some of these terms have gained wide use and acceptance, although they are not always used with precisely the same meaning.

The USGS collects information about the quantity and quality of all mineral resources. In 1976, the USGS and the U.S. Bureau of Mines developed a common classification and nomenclature, which was published as USGS Bulletin 1450–A—“Principles of the Mineral Resource Classification System of the U.S. Bureau of Mines and U.S. Geological Survey.” Experience with this resource classification system showed that some changes were necessary in order to make it more workable in practice and more useful in long-term planning. Therefore, representatives of the USGS and the U.S. Bureau of Mines collaborated to revise Bulletin 1450–A. Their work was published in 1980 as USGS Circular 831—“Principles of a Resource/Reserve Classification for Minerals.”

Long-term public and commercial planning must be based on the probability of discovering new deposits, on developing economic extraction processes for currently unworkable deposits, and on knowing which resources are immediately available. Thus, resources must be continuously reassessed in the light of new geologic knowledge, of progress in science and technology, and of shifts in economic and political conditions. To best serve these planning needs, known resources should be classified from two standpoints: (1) purely geologic or physical/chemical characteristics—such as grade, quality, tonnage, thickness, and depth—of the material in place; and (2) profitability analyses based on costs of extracting and marketing the material in a given economy at a given time. The former constitutes important objective scientific information of the resource and a relatively unchanging foundation upon which the latter more valuable economic delineation can be based.

The revised classification system, designed generally for all mineral materials, is shown graphically in figures 1 and 2; its components and their usage are described in the text. The classification of mineral and energy resources is necessarily arbitrary because definitional criteria do not always coincide with natural boundaries. The system can be used to report the status of mineral and energy-fuel resources for the Nation or for specific areas.1

Resource-Preserving Definitions

A dictionary definition of resource, “something in reserve or ready if needed,” has been adapted for mineral and energy resources to comprise all materials, including those only surmised to exist, that have present or anticipated future value.

Resource.—A concentration of naturally occurring solid, liquid, or gaseous material in or on the Earth’s crust in such form and amount that economic extraction of a commodity from the concentration is currently or potentially feasible

Original Resource.—The amount of a resource before production.

Identified Resources.—Resources whose location, grade, quality, and quantity are known or estimated from specific geologic evidence. Identified resources include economic, marginally economic, and subeconomic components. To reflect varying degrees of geologic certainty, these economic divisions can be subdivided into measured, indicated, and inferred.

Demonstrated.—A term for the sum of measured plus indicated.

Measured.—Quantity is computed from dimensions revealed in outcrops, trenches, workings, or drill holes; grade and(or) quality are computed from the results of detailed sampling. The sites for inspection, sampling, and measurements are spaced so closely and the geologic character is so well defined that size, shape, depth, and mineral content of the resource are well established.

Indicated.—Quantity and grade and(or) quality are computed from information similar to that used for measured resources, but the sites for inspection, sampling, and measurement are farther apart or are otherwise less adequately spaced. The degree of assurance, although lower than that for measured resources, is high enough to assume continuity between points of observation.

Inferred.—Estimates are based on an assumed continuity beyond measured and(or) indicated resources, for which there is geologic evidence. Inferred resources may or may not be supported by samples or measurements.

Reserve Base.—That part of an identified resource that meets specified minimum physical and chemical criteria related to current mining and production practices, including those for grade, quality, thickness, and depth. The reserve base is the inplace demonstrated (measured plus indicated) resource from which reserves are estimated. It may encompass those parts of the resources that have a reasonable potential for becoming economically available within planning horizons beyond those that assume proven technology and current economics. The reserve base includes those resources that are currently economic (reserves), marginally economic (marginal reserves), and some of those that are currently subeconomic (subeconomic resources). The term “geologic reserve” has been applied by others generally to the reserve-base category, but it also may include the inferred-reserve-base category; it is not a part of this classification system

Inferred Reserve Base.—The in-place part of an identified resource from which inferred reserves are estimated. Quantitative estimates are based largely on knowledge of the geologic character of a deposit and for which there may be no samples or measurements. The estimates are based on an assumed continuity beyond the reserve base, for which there is geologic evidence.

Reserves.—That part of the reserve base which could be economically extracted or produced at the time of determination. The term reserves need not signify that extraction facilities are in place and operative. Reserves include only recoverable materials; thus, terms such as “extractable reserves” and “recoverable reserves” are redundant and are not a part of this classification system

Marginal Reserves.—That part of the reserve base which, at the time of determination, borders on being economically producible. Its essential characteristic is economic uncertainty. Included are resources that would be producible, given postulated changes in economic or technological factors.

Economic.—This term implies that profitable extraction or production under defined investment assumptions has been established, analytically demonstrated, or assumed with reasonable certainty

Subeconomic Resources.—The part of identified resources that does not meet the economic criteria of reserves and marginal reserves

Undiscovered Resources.—Resources, the existence of which are only postulated, comprising deposits that are separate from identified resources. Undiscovered resources may be postulated in deposits of such grade and physical location as to render them economic, marginally economic, or subeconomic. To reflect varying degrees of geologic certainty, undiscovered resources may be divided into two parts:

Hypothetical Resources.—Undiscovered resources that are similar to known mineral bodies and that may be reasonably expected to exist in the same producing district or region under analogous geologic conditions. If exploration confirms their existence and reveals enough information about their quality, grade, and quantity, they will be reclassified as identified resources.

Speculative Resources.—Undiscovered resources that may occur either in known types of deposits in favorable geologic settings where mineral discoveries have not been made, or in types of deposits as yet unrecognized for their economic potential. If exploration confirms their existence and reveals enough information about their quantity, grade, and quality, they will be reclassified as identified resources.

Restricted Resources/Reserves.—That part of any resource/reserve category that is restricted from extraction by laws or regulations. For example, restricted reserves meet all the requirements of reserves except that they are restricted from extraction by laws or regulations.

Other Occurrences.—Materials that are too low grade or for other reasons are not considered potentially economic, in the same sense as the defined resource, may be recognized and their magnitude estimated, but they are not classified as resources. A separate category, labeled other occurrences, is included in figures 1 and 2. In figure 1, the boundary between subeconomic and other occurrences is limited by the concept of current or potential feasibility of economic production, which is required by the definition of a resource. The boundary is obviously uncertain, but limits may be specified in terms of grade, quality, thickness, depth, percent extractable, or other economic-feasibility variables

Cumulative Production.—The amount of past cumulative production is not, by definition, a part of the resource. Nevertheless, a knowledge of what has been produced is important in order to understand current resources, in terms of both the amount of past production and the amount of residual or remaining in-place resource. A separate space for cumulative production is shown in figures 1 and 2. Residual material left in the ground during current or future extraction should be recorded in the resource category appropriate to its economic-recovery potential.

Figure 1 Major Elements of Mineral-Resource Classification, Excluding Reserve Base and Inferred Reserve Base

MCS2015AppendixCFigure1.png

Figure 2 Reserve Base and Inferred Reserve Base Classification Categories

MCS2015AppendixCFigure2.png

Part B—Sources of Reserve Data

National information on reserves for most mineral commodities found in this report, including those for the United States, is derived from a variety of sources. The ideal source of such information would be comprehensive evaluations that apply the same criteria to deposits in different geographic areas and report the results by country. In the absence of such evaluations, national reserve estimates compiled by countries for selected mineral commodities are a primary source of national reserves information. Lacking national assessment information by governments, sources such as academic articles, company reports, presentations by company representatives, and trade journal articles, or a combination of these, serve as the basis for national information on reserves reported in the mineral commodity sections of this publication.

A national estimate may be assembled from the following: historically reported reserve information carried for years without alteration because no new information is available, historically reported reserves reduced by the amount of historical production, and company reported reserves. International minerals availability studies conducted by the U.S. Bureau of Mines before 1996 and estimates of identified resources by an international collaborative effort (the International Strategic Minerals Inventory) are the bases for some reserve estimates. The USGS collects information about the quantity and quality of mineral resources but does not directly measure reserves, and companies or governments do not directly report reserves to the USGS. Reassessment of reserves is a continuing process, and the intensity of this process differs for mineral commodities, countries, and time period.

Some countries have specific definitions for reserve data, and reserves for each country are assessed separately, based on reported data and definitions. An attempt is made to make reserves consistent among countries for a mineral commodity and its byproducts. For example, the Australasian Joint Ore Reserves Committee (JORC) established the Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (the JORC Code) that sets out minimum standards, recommendations, and guidelines for public reporting in Australasia of exploration results, mineral resources, and ore reserves. Companies listed on the Australian Securities Exchange and the New Zealand Stock Exchange are required to report publicly on ore reserves and mineral resources under their control, using the JORC Code (http://www.jorc.org/).

Data reported for individual deposits by mining companies are compiled in Geoscience Australia’s national mineral resources database and used in the preparation of the annual national assessments of Australia’s mineral resources. Because of its specific use in the JORC Code, the term “reserves” is not used in the national inventory, where the highest category is “Economic Demonstrated Resources” (EDR). In essence, EDR combines the JORC Code categories proved reserves and probable reserves, plus measured resources and indicated resources. This is considered to provide a reasonable and objective estimate of what is likely to be available for mining in the long term. Accessible Economic Demonstrated Resources represent the resources within the EDR category that are accessible for mining. Reserves for Australia in Mineral Commodity Summaries 2015 are Accessible EDR. For more information, see Australia’s Identified Mineral Resources 2013 (http://www.ga.gov.au/corporate_data/..._AIMR_2013.pdf).

In Canada, the Canadian Institute of Mining, Metallurgy, and Petroleum (CIM) provides definition standards for the classification of mineral resources and mineral reserves estimates into various categories. The category to which a resource or reserve estimate is assigned depends on the level of confidence in the geologic information available on the mineral deposit, the quality and quantity of data available on the deposit, the level of detail of the technical and economic information that has been generated about the deposit, and the interpretation of the data and information. For more information on the CIM definition standards, see http://www.cim.org/en/News-and-Event...idance-updated.

Russian reserves for most minerals, which had been withheld, have been released with increasing frequency within the past few years and can appear in a number of sources, although no systematic list of Russian reserves is published. Russian reserve data for various minerals appear at times in journal articles, such as those in the journal Mineral’nye Resursy Rossii [Mineral Resources of Russia (MRR)], which is published by the Russian Ministry of Natural Resources. Russian reserve data are often published according to the Soviet reserves classification system, which is still used in many countries of the former Soviet Union but also at times published according to the JORC system based on analyses made by Western firms. It is sometimes not clear if the reserves are being reported in ore or mineral content. It is also in many cases not clear which definition of reserves is being used, as the system inherited from the former Soviet Union has a number of ways in which the term reserves is defined, and these definitions qualify the percentage of reserves that are included. For example, the Soviet reserves classification system, besides the categories A, B, C1, and C2, which represent progressively detailed knowledge of a mineral deposit based on exploration data, has other subcategories cross-imposed upon the system. Under the broad category reserves (zapasy), there are subcategories that include balance reserves (economic reserves or balansovye zapasy) and outside the balance reserves (uneconomic reserves or zabalansovye zapasy), as well as categories that include explored, industrial, and proven reserves, and the reserves totals can vary significantly, depending on the specific definition of reserves being reported.

Appendix D—Country Specialists Directory

Minerals information country specialists at the U.S. Geological Survey collect and analyze information on the mineral
industries of more than 170 nations throughout the world. The specialists are available to answer minerals-related
questions concerning individual countries.

Africa and the Middle East

Algeria Mowafa Taib
Angola Omayra Bermúdez-Lugo
Bahrain Waseem Abdulameer
Benin Philip M. Mobbs
Botswana Thomas R. Yager
Burkina Faso Omayra Bermúdez-Lugo
Burundi Thomas R. Yager
Cameroon Philip M. Mobbs
Cabo Verde Philip M. Mobbs
Central African Republic Omayra Bermúdez-Lugo
Chad Philip M. Mobbs
Comoros Philip M. Mobbs
Congo (Brazzaville) Philip M. Mobbs
Congo (Kinshasa) Thomas R. Yager
Côte d’Ivoire Omayra Bermúdez-Lugo
Djibouti Mowafa Taib
Egypt Mowafa Taib
Equatorial Guinea Philip M. Mobbs
Eritrea Thomas R. Yager
Ethiopia Thomas R. Yager
Gabon Waseem Abdulameer
The Gambia Philip M. Mobbs
Ghana Omayra Bermúdez-Lugo
Guinea Omayra Bermúdez-Lugo
Guinea-Bissau Philip M. Mobbs
Iran Philip M. Mobbs
Iraq Waseem Abdulameer
Israel Thomas R. Yager
Jordan Mowafa Taib
Kenya Thomas R. Yager
Kuwait Waseem Abdulameer
Lebanon Mowafa Taib
Lesotho Philip M. Mobbs
Liberia Omayra Bermúdez-Lugo
Libya Mowafa Taib
Madagascar Thomas R. Yager
Malawi Thomas R. Yager
Mali Omayra Bermúdez-Lugo
Mauritania Mowafa Taib
Mauritius Philip M. Mobbs
Morocco & Western Sahara Mowafa Taib
Mozambique Thomas R. Yager
Namibia Omayra Bermúdez-Lugo
Niger Omayra Bermúdez-Lugo
Nigeria Philip M. Mobbs
Oman Waseem Abdulameer
Qatar Waseem Abdulameer
Reunion Philip M. Mobbs
Rwanda Thomas R. Yager
São Tomé & Principe Philip M. Mobbs
Saudi Arabia Waseem Abdulameer
Senegal Omayra Bermúdez-Lugo
Seychelles Philip M. Mobbs
Sierra Leone Omayra Bermúdez-Lugo
Somalia Thomas R. Yager
South Africa Thomas R. Yager
South Sudan Thomas R. Yager
Sudan Mowafa Taib
Swaziland Philip M. Mobbs
Syria Mowafa Taib
Tanzania Thomas R. Yager
Togo Omayra Bermúdez-Lugo
Tunisia Mowafa Taib
Uganda Thomas R. Yager
United Arab Emirates Waseem Abdulameer
Yemen Waseem Abdulameer
Zambia Philip M. Mobbs
Zimbabwe Philip M. Mobbs

Asia and the Pacific

Afghanistan Karine Renaud
Australia Pui-Kwan Tse
Bangladesh Yolanda Fong-Sam
Bhutan Yolanda Fong-Sam
Brunei Pui-Kwan Tse
Burma (Myanmar) Yolanda Fong-Sam
Cambodia Yolanda Fong-Sam
China Pui-Kwan Tse
East Timor Pui-Kwan Tse
Fiji Lin Shi
India Karine Renaud
Indonesia Susan Wacaster
Japan Susan Wacaster
Korea, North Susan Wacaster
Korea, Republic of Susan Wacaster
Laos Yolanda Fong-Sam
Malaysia Pui-Kwan Tse
Mongolia Lin Shi
Nauru Pui-Kwan Tse
Nepal Yolanda Fong-Sam
New Caledonia Susan Wacaster
New Zealand Pui-Kwan Tse
Pakistan Karine Renaud
Papua New Guinea Susan Wacaster
Philippines Yolanda Fong-Sam
Singapore Pui-Kwan Tse
Solomon Islands Karine Renaud
Sri Lanka Karine Renaud
Taiwan Pui-Kwan Tse
Thailand Yolanda Fong-Sam
Vietnam Yolanda Fong-Sam

Europe and Central Eurasia

Albania Sinan Hastorun
Armenia 1 Elena Safirova
Austria 2 Sinan Hastorun
Azerbaijan 1 Elena Safirova
Belarus 1 Elena Safirova
Belgium 2 Alberto A. Perez
Bosnia and Herzegovina Sean Xun
Bulgaria 2 Sean Xun
Croatia 2 Sinan Hastorun
Cyprus 2 Sinan Hastorun
Czech Republic 2 Sean Xun
Denmark, Faroe Islands,
and Greenland 2 Alberto A. Perez
Estonia 2 Lin Shi
Finland 2 Alberto A. Perez
France 2 Alberto A. Perez
Georgia Elena Safirova
Germany 2 Alberto A. Perez
Greece 2 Lin Shi
Hungary 2 Sinan Hastorun
Iceland Alberto A. Perez
Ireland 2 Alberto A. Perez
Italy 2 Alberto A. Perez
Kazakhstan 1 Elena Safirova
Kosovo Sinan Hastorun
Kyrgyzstan 1 Karine Renaud
Latvia 2 Lin Shi
Lithuania 2 Lin Shi
Luxembourg 2 Alberto A. Perez
Macedonia Sean Xun
Malta 2 Sinan Hastorun
Moldova 1 Elena Safirova
Montenegro Sinan Hastorun
Netherlands 2 Alberto A. Perez
Norway Alberto A. Perez
Poland 2 Sean Xun
Portugal 2 Sean Xun
Romania 2 Sean Xun
Russia 1 Elena Safirova
Serbia Sean Xun
Slovakia 2 Lin Shi
Slovenia 2 Sean Xun
Spain 2 Yadira Soto-Viruet
Sweden 2 Alberto A. Perez
Switzerland Sinan Hastorun
Tajikistan1 Karine Renaud
Turkey Sinan Hastorun
Turkmenistan 1 Karine Renaud
Ukraine 1 Elena Safirova
United Kingdom 2 Alberto A. Perez
Uzbekistan 1 Elena Safirova

1 Member of Commonwealth of Independent States.
2 Member of European Union.

North America, Central America, and the Caribbean

Aruba Yadira Soto-Viruet
Belize Susan Wacaster
Bermuda Yadira Soto-Viruet
Canada Philip M. Mobbs
Costa Rica Susan Wacaster
Cuba Yadira Soto-Viruet
Dominican Republic Yadira Soto-Viruet
El Salvador Susan Wacaster
Guatemala Susan Wacaster
Haiti Yadira Soto-Viruet
Honduras Susan Wacaster
Jamaica Yadira Soto-Viruet
Mexico Yadira Soto-Viruet
Nicaragua Susan Wacaster
Panama Susan Wacaster
Trinidad and Tobago Yadira Soto-Viruet

South America

Argentina Susan Wacaster
Bolivia Susan Wacaster
Brazil Yadira Soto-Viruet
Chile Susan Wacaster
Colombia Susan Wacaster
Ecuador Susan Wacaster
French Guiana Philip M. Mobbs
Guyana Philip M. Mobbs
Paraguay Yadira Soto-Viruet
Peru Yadira Soto-Viruet
Suriname Philip M. Mobbs
Uruguay Yadira Soto-Viruet
Venezuela Yadira Soto-Viruet

Country specialist, Telephone, & E-mail
Country specialist Telephone E-mail
Waseem Abdulameer (703) 648-7747 wabdulameer@usgs.gov
Omayra Bermúdez-Lugo (703) 648–4946 obermude@usgs.gov
Yolanda Fong-Sam (703) 648–7756 yfong-sam@usgs.gov
Sinan Hastorun (703) 648–7744 shastorun@usgs.gov
Philip M. Mobbs (703) 648–7740 pmobbs@usgs.gov
Alberto A. Perez (703) 648–7749 aperez@usgs.gov
Karine Renaud (703) 648--7748 krenaud@usgs.gov
Elena Safirova (703) 648–7731 esafirova@usgs.gov
Lin Shi (703) 648–7994 lshi@usgs.gov
Yadira Soto-Viruet (703) 648–4957 ysoto-viruet@usgs.gov
Mowafa Taib (703) 648–4986 mtaib@usgs.gov
Pui-Kwan Tse (703) 648–7750 ptse@usgs.gov
Susan Wacaster (703) 648–7785 swacaster@usgs.gov
Sean Xun (703) 648-7746 sxun@usgs.gov
Thomas R. Yager (703) 648–7739 tyager@usgs.gov

Mineral Commodities

Abrasives (Manufactured)

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(Fused aluminum oxide and silicon carbide)

(Data in metric tons unless otherwise noted)

Domestic Production and Use: Fused aluminum oxide was produced by two companies at three plants in the United States and Canada. Production of regular-grade fused aluminum oxide had an estimated value of $2 million. Silicon carbide was produced by two companies at two plants in the United States. Domestic production of crude silicon carbide had an estimated value of about $26 million. Bonded and coated abrasive products accounted for most abrasive uses of fused aluminum oxide and silicon carbide.

Table Salient Statistics—United States
Year 2010 2011 2012 2013 2014 e
Production,1 United States and Canada (crude):          
Fused aluminum oxide, regular 10,000 10,000 10,000 10,000 10,000
Silicon carbide 35,000 35,000 35,000 35,000 35,000
Imports for consumption (U.S.):          
Fused aluminum oxide 185,000 223,000 231,000 184,000 150,000
Silicon carbide 143,000 129,000 100,000 119,000 139,000
Exports (U.S.):          
Fused aluminum oxide 20,000 19,900 19,100 22,000 20,000
Silicon carbide 23,100 27,800 20,000 18,400 21,100
Consumption, apparent (U.S.):          
Fused aluminum oxide NA NA NA NA NA
Silicon carbide 155,000 136,000 115,000 136,000 153,000
Price, value of imports, dollars per ton (U.S.):          
Fused aluminum oxide, regular 555 627 560 661 670
Fused aluminum oxide, high-purity 1,300 1,360 1,080 1,660 1,410
Silicon carbide 793 1,260 877 638 641
Net import reliance 2 as a percentage of apparent consumption (U.S.):          
Fused aluminum oxide NA NA NA NA NA
Silicon carbide 77 74 70 74 77

Recycling: Up to 30% of fused aluminum oxide may be recycled, and about 5% of silicon carbide is recycled.

Import Sources (2010–13): Fused aluminum oxide, crude: China, 79%; Venezuela, 12%; Canada, 6%; and other, 3%. Fused aluminum oxide, grain: Germany, 19%; Brazil, 18%; Austria, 16%; Canada, 13%; and other, 34%. Silicon carbide, crude: China, 60%; South Africa, 17%; the Netherlands, 7%; Romania, 7%; and other, 9%. Silicon carbide, grain: China, 43%; Brazil, 24%; Russia, 10%; Norway, 7%; and other, 16%.

Table Tariff Item
Tariff Item Number Normal Trade Relations 12–31–14
Fused aluminum oxide, crude 2818.10.1000 Free
White, pink, ruby artificial corundum, greater than 97.5% fused aluminum oxide, grain 2818.10.2010 1.3% ad value
Artificial corundum, not elsewhere specified or included, fused aluminum oxide, grain 2818.10.2090 1.3% ad value
Silicon carbide, crude 2849.20.1000 Free
Silicon carbide, grain 2849.20.2000 0.5% ad value

Depletion Allowance: None.

Government Stockpile: None.

Prepared by Donald W. Olson [(703) 648–7721, dolson@usgs.gov]

Events, Trends, and Issues: In 2014, China was the world’s leading producer of abrasive fused aluminum oxide and abrasive silicon carbide, with production nearly at capacity. Imports and higher operating costs than in China continued to challenge abrasives producers in the United States and Canada. Foreign competition, particularly from China, is expected to persist and continue to limit production in North America. Abrasives markets are greatly influenced by activity in the manufacturing sector in the United States. During 2014, these manufacturing sectors included the aerospace, automotive, furniture, housing, and steel industries, all of which experienced increased production. The U.S. abrasive markets also are influenced by economic and technological trends.

Table World Capacity Production
Mineral and Year Fused aluminum oxide 2013 Fused aluminum oxide 2014 e Silicon carbide 2013 Silicon carbide 2014 e
United States and Canada 60,400 60,400 42,600 42,600
Argentina 5,000 5,000
Australia 50,000 50,000
Austria 60,000 60,000
Brazil 50,000 50,000 43,000 43,000
China 700,000 800,000 455,000 455,000
France 40,000 40,000 16,000 16,000
Germany 80,000 80,000 36,000 36,000
India 40,000 40,000 5,000 5,000
Japan 25,000 25,000 60,000 60,000
Mexico 45,000 45,000
Norway 80,000 80,000
Venezuela 30,000 30,000
Other countries 80,000 80,000 190,000 190,000
World total (rounded) 1,190,000 1,290,000 1,010,000 1,010,000

World Resources: Although domestic resources of raw materials for the production of fused aluminum oxide are rather limited, adequate resources are available in the Western Hemisphere. Domestic resources are more than adequate for the production of silicon carbide.

Substitutes: Natural and manufactured abrasives, such as garnet, emery, or metallic abrasives, can be substituted for fused aluminum oxide and silicon carbide in various applications.

e Estimated. NA Not available. — Zero.

1 Rounded to the nearest 5,000 tons to protect proprietary data.

2 Defined as imports – exports.

Aluminum

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Antimony

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Arsenic

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Asbestos

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Barite

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Bauxite and Alumina

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Beryllium

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Bismuth

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Boron

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Bromine

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Cadmium

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Cement

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Cesium

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Chromium

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Clays

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Cobalt

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Copper

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Diamond (Industrial)

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Diatomite

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Feldspar

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Fluorspar

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Gallium

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Garnet (Industrial)

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Gemstones

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Germanium

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Gold

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Graphite (Natural)

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Gypsum

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Helium

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Indium

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Iodine

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Iron and Steel

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Iron and Steel Scrap

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Iron and Steel Slag

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Iron Ore

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Iron Oxide Pigments

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Kyanite and Related Minerals

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Lead

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Lime

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Lithium

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Magnesium Compounds

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Magnesium Metal

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Manganese

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Mercury

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Mica (Natural)

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Molybdenum

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Nickel

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Niobium (Columbium)

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Nitrogen (Fixed)—Ammonia

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Peat

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Perlite

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Phosphate Rock

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Platinum-Group Metals

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Potash

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Pumice and Pumicite

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Quartz Crystal (Industrial)

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Rare Earths

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Rhenium

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Rubidium

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Salt

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Sand and Gravel (Construction)

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Sand and Gravel (Industrial)

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Scandium

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Selenium

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Silicon

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Silver

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Soda Ash

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Stone (Crushed)

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Stone (Dimension)

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Strontium

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Sulfur

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Talc and Pyrophyllite

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Tantalum

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Tellurium

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Thallium

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Thorium

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Tin

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Titanium and Titanium Dioxide

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Titanium Mineral Concentrates

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Tungsten

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Vanadium

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Vermiculite

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Wollastonite

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Yttrium

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Zeolites (Natural)

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Zinc

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Zirconium and Hafnium

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National Geochemical Survey Database

Source: http://mrdata.usgs.gov/geochem/

National-scale geochemical analysis of stream sediments and soils in the US, from existing data, reanalysis of existing samples, and new sampling. Goal for sample density is one per 289 square km.

View:
Show in a web browser window:
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Continental US Alaska
Show in Google Earth or download KML:
KMZcompressed, 2.2M bytes
Show in your GIS using OGC WMS:
http://mrdata.usgs.gov/services/ngs?request=GetCapabilities&service=WMS&version=1.1.1
Download:
Download data for geographic areas you choose
Notes on using these data within ArcGIS
Get the entire data set
  • Shapefile with a subset of 53 attributes: ICP40, As, Se, Hg (74,409 samples, 5.2MB .ZIP package) My Note: Downloaded this.
  • dBase file with all 287 attributes (77,212 records, 19.6MB .ZIP package)
  • CSV file with all 287 attributes (77,212 records, 13MB .ZIP package) My Note: Downloaded this.
Documentation:
National Geochemical Survey - Full documentation
Complete report on the web including summaries of component datasets used to compile this resource, maps showing county-by- county average concentration of elements, and comprehensive explanations of the analytical methods.
Metadata:
[Outline] - [Questions & Answers] - [Plain text]
About the database fields
Related
topics

 

AluminumAntimonyArsenicBariumBerylliumBismuthBoronBromineCadmiumCalciumCarbonCeriumCesiumChemical analysisChlorineChromiumCobaltCopper,DysprosiumEuropiumFluorineGalliumGeochemistryGeospatial datasetsGoldHafniumIronLanthanumLeadLithiumLutetiumMagnesiumManganeseMercury,MolybdenumNeodymiumNickelNiobiumPalladiumPhosphorusPlatinumPotassiumPraseodymiumRubidiumSamariumScandiumSeleniumSiliconSilverSodium,StrontiumSulfurTantalumTelluriumTerbiumThalliumThoriumTinTitaniumTungstenUnconsolidated depositsUraniumVanadiumYtterbiumYttriumZincZirconium
Columnar textDBFHTML tableKMLOGC WFSOGC WMSShapefile

 

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Mineral Resources Data System (MRDS)

 

Source: http://mrdata.usgs.gov/mrds/

 

MRDS is a collection of reports describing metallic and nonmetallic mineral resources throughout the world. Included are deposit name, location, commodity, deposit description, geologic characteristics, production, reserves, resources, and references. It subsumes the original MRDS and MAS/MILS.

MRDS is large, complex, and somewhat problematic. This service provides a subset of the database comprised of those data fields deemed most useful and which most frequently contain some information, but full reports of most records are available as well.

Current status: As of 2011, USGS has ceased systematic updates to MRDS, and is working to create a new database, focused primarily on the conterminous US. For locations outside the United States, MRDS remains the best collection of reports that USGS has available. For locations in Alaska, the Alaska Resource Data File remains the most coherent collection of such reports and is in continuing development.
View:
Show in a web browser window:
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Continental US Global by commodity
Show in Google Earth or download KML:
(Instructions and advice)
Show in your GIS using OGC WMS:
http://mrdata.usgs.gov/services/mrds?request=GetCapabilities&service=WMS&version=1.1.1
Download:
Download data for geographic areas you choose
Search by site name, location, or commodity
Notes on using MRDS within ArcGIS
Options for downloading the entire data set depend on what software you want to use:
Spreadsheet
mrds-csv.zip: Comma-separated values, 23 MB expands to 125 MB
All records, 44 best data fields, multiple values within a field separated by semicolon
Geographic information system
mrds.zip: Shapefile, 40 MB expands to 1.1 GB
All records, 44 best data fields, multiple values within a field separated by semicolon, long text fields truncated at 254 characters
mrds-us.zip: Shapefile, 34 MB expands to 932 MB
US records only, 44 best data fields, multiple values within a field separated by semicolon, long text fields truncated at 254 characters
mrds-gdb.zip: File geodatabase, 39 MB expands to 250 MB
All records; location, site names, commodities, minerals; separate tables
mrds-mdb.zip: Personal geodatabase (.mdb), 67 MB expands to 293 MB
All records; location, site names, commodities, minerals; separate tables
Relational database
rdbms-tab.zip: Tab-delimited tables, 20 MB expands to 90 MB
All records; location, site names, commodities, minerals; separate tables
rdbms-tab-all.zip: Tab-delimited tables, 118 MB expands to 804 MB
All records; all tables; separate tables
Documentation:
Metadata:
[Outline] - [Questions & Answers] - [Plain text]
About the database fields
Best 44 fields
Most commonly requested and best populated. Provided by default through the data selection and download interfaces above
Compact geodatabase fields
Provided in the File geodatabase and personal geodatabase downloads
Comprehensive fields
Provided only through the comprehensive relational database download package rdbms-tab-all.zip
Commodity codes
[HTML] - [Tab-delimited text]

 

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