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TerraPop Vision

TerraPop Vision. An organizational and technical framework to preserve , integrate , disseminate , and analyze global-scale spatiotemporal data describing population and the environment. Develop tools to make data interoperable across data formats and subject areas

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TerraPop Vision

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  1. TerraPop Vision An organizational and technical framework to preserve, integrate, disseminate, and analyze global-scale spatiotemporal data describing population and the environment. • Develop tools to make data interoperable across data formats and subject areas • Break down disciplinary silos

  2. TerraPop Goals Lowerbarriers to conducting interdisciplinary human-environment interactions research by making data with different formats from different scientific domains easily interoperable

  3. Source Data Domains & Formats Population Microdata Area-Level Data

  4. Making disparate data formats interoperable Microdata: Characteristics of individuals and households Area-level data:Characteristics of places defined by boundaries Raster data: Values tied to spatial coordinates

  5. Age Birthplace Mother’s birthplace Sex Relationship Race Occupation Microdata Structure Geographic and housing characteristics Household record (shaded) followed by a person record for each member of the household For each type of record, columns correspond to specific variables

  6. Khartoum, CBS-Sudan

  7. 1973 Census Tapes arrive at Muller Media (New York) via Barcelona

  8. Dhaka, Bangladesh Bureau of Statistics

  9. The Power of Microdata • Customized measures: Variables based on combined characteristics of family and household members, capitalizing on the hierarchical structure of the data • Multivariate analysis: Analyze many individual, household, and community characteristics simultaneously • Interoperability: Harmonize data across time and space Age classification for school enrollment in published U.S. Census

  10. Growth of Public-Use Microdata (number of person-records available) We are Here

  11. IPUMS-International Microdata Over 100 Collaborating National Statistical Agencies

  12. Area Level (Vector) Data Describing characteristics of geographic polygons Median Household Income by Census Tract

  13. Area-level Data Sources • Census tables, especially where microdata is unavailable • Other types of surveys, data • Agricultural surveys • Economic surveys, data • Election data • Disease data • Legal/policy information • Environmental policy • Social policy • Human rights

  14. Raster Data Represented as pixels in a grid Mean Precipitation

  15. Raster Data • Beta system • Global Land Cover 2000 • Harvested Area and Yield for 175 crops (Global Landscapes Initiative) • Temperature and precipitation (WorldClim) • Future additions • Additional LU/LC and climate datasets • Elevation • Vegetation characteristics • Bioclimatic & ecologic zones

  16. Location-Based Integration Microdata  Area-level  Raster

  17. Location-Based Integration Microdata Mix and match variables originating in any of the data structures Obtain output in the data structure most useful to you Area-level data Rasters

  18. Location-Based Integration Microdata Individuals and households with their environmental and social context Area-level data Rasters

  19. Location-Based Integration Microdata Summarized environmental and population characteristics for administrative districts Area-level data Rasters

  20. Location-Based Integration Microdata Rasters of population and environment data Area-level data Rasters

  21. Area-Level Summary of Raster Data

  22. Rasterization of Area-Level Data

  23. Rasterization • Beta system – Uniform distribution assumption • Use lowest level units available • Rates – same value for all cells in unit • Counts – evenly distributed across cells in unit • Future – Distribute based on ancillary data • Requires research on available methods • May provide as service – users select: • Ancillary data • Weights • Spatial distribution parameters

  24. Data Access System

  25. General Workflow • Browse variables and metadata • Select variables and datasets • View data cart contents • Select output options

  26. Prototype Data Access System

  27. Variable Groups

  28. Variable Browsing

  29. Variable Metadata

  30. To join the beta test email terrapop@umn.edu

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