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David Van Riper
RDAP14, San Diego
March 27, 2014
TerraPop Goals
Lower barriers to conducting interdisciplinary human-
environment interactions research by making data with
different formats from different scientific domains easily
interoperable
Provide an organizational and technical framework to
preserve, integrate, disseminate, and analyze global-
scale spatiotemporal data describing population and the
environment.
TerraPop in Context
Collaborating Organizations
• Data integration expertise
• Large census and survey
data collections & expertise
• Institutional foundation
• Human-environment
interactions research
expertise
• Environmentally-oriented
data collections & expertise
• Data preservation and
sustainability expertise
• Social science data
collections & expertise
• Major producers and distributors of data on both humans and their environment
• Major producers of tools for integrating and transforming data across formats
• Leaders in preservation and sustainability
TerraPop in Context
DataNet Cyberinfrastructure
Curated population and
environment data collection
 Exposed through DataONE,
SEAD
 Extracts exportable to DFC
Integration services
 Potentially available through
DFC, SEAD
 Open source components and
API
• T W O D O M AI N S : P O P U L AT I O N & E N V I R O N M E N T
• T H R E E D ATA S T R U C T U R E S
• Microdata
• Area-level data
• Rasters
Source Data
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
M I C R O D ATA  AR E A- L E V E L  R AS T E R
Location-Based Integration
Location-Based Integration
Microdata
Area-level dataRasters
Mix and match
variables originating in
any of the data structures
Obtain output in the
data structure most
useful to you
Location-Based Integration
Individuals and households
with their environmental
and social context
Microdata
Area-level dataRasters
Location-Based Integration
Summarized
environmental
and population
Microdata
Area-level dataRasters
County ID
G17003100001
G17003100002
G17003100003
G17003100004
G17003100005
G17003100006
G17003100007
County ID
Mean Ann.
Temp.
Max. Ann.
Precip.
G17003100001 21.2 768
G17003100002 23.4 589
G17003100003 24.3 867
G17003100004 21.5 943
G17003100005 24.1 867
G17003100006 24.4 697
G17003100007 25.6 701
County ID
Mean Ann.
Temp.
Max. Ann.
Precip.
Rent,
Rural
Rent,
Urban
Own,
Rural
Own,
Urban
G17003100001 21.2 768 3129 1063 637 365
G17003100002 23.4 589 2949 1075 1469 717
G17003100003 24.3 867 3418 1589 1108 617
G17003100004 21.5 943 1882 425 202 142
G17003100005 24.1 867 2416 572 426 197
G17003100006 24.4 697 2560 934 950 563
G17003100007 25.6 701 2126 653 321 215
characteristics for
administrative
districts
Location-Based Integration
Rasters of
population and
environment
data
Microdata
Area-level dataRasters
Future Plans
Collection Expansion
 Add more census/survey data
 Add more global environmental data
 Add more GIS mapping files
 Develop data curation protocol(s) for adding
additional data to TerraPop
 Develop mechanisms for scholars to deposit
data/metadata into TerraPop
 Allow others’ data to be integrated with other TerraPop data
Upcoming Activities
 Beta system public release – soon!
 User interface redesign for Fall 2014
 Conference workshops
 IASSIST – Toronto – June 3, 2014
 Population Association of America – Boston – April 30, 2014
 More to come in last 2014/early 2015
 Become a DataONE member node
 Continue working with SEAD and DFC on
potential collaborations
Keep in touch with TerraPop
-Website: http://www.terrapop.org
-Data access system: http://beta.terrapop.org
-Twitter: @TerraPopulus
-Email: David Van Riper – vanriper@umn.edu
RDAP14: David Van Riper of Terra Populus

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RDAP14: David Van Riper of Terra Populus

  • 1. David Van Riper RDAP14, San Diego March 27, 2014
  • 2. TerraPop Goals Lower barriers to conducting interdisciplinary human- environment interactions research by making data with different formats from different scientific domains easily interoperable Provide an organizational and technical framework to preserve, integrate, disseminate, and analyze global- scale spatiotemporal data describing population and the environment.
  • 3. TerraPop in Context Collaborating Organizations • Data integration expertise • Large census and survey data collections & expertise • Institutional foundation • Human-environment interactions research expertise • Environmentally-oriented data collections & expertise • Data preservation and sustainability expertise • Social science data collections & expertise • Major producers and distributors of data on both humans and their environment • Major producers of tools for integrating and transforming data across formats • Leaders in preservation and sustainability
  • 4. TerraPop in Context DataNet Cyberinfrastructure Curated population and environment data collection  Exposed through DataONE, SEAD  Extracts exportable to DFC Integration services  Potentially available through DFC, SEAD  Open source components and API
  • 5. • T W O D O M AI N S : P O P U L AT I O N & E N V I R O N M E N T • T H R E E D ATA S T R U C T U R E S • Microdata • Area-level data • Rasters Source Data
  • 6. 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
  • 7. M I C R O D ATA  AR E A- L E V E L  R AS T E R Location-Based Integration
  • 8. Location-Based Integration Microdata Area-level dataRasters Mix and match variables originating in any of the data structures Obtain output in the data structure most useful to you
  • 9. Location-Based Integration Individuals and households with their environmental and social context Microdata Area-level dataRasters
  • 10. Location-Based Integration Summarized environmental and population Microdata Area-level dataRasters County ID G17003100001 G17003100002 G17003100003 G17003100004 G17003100005 G17003100006 G17003100007 County ID Mean Ann. Temp. Max. Ann. Precip. G17003100001 21.2 768 G17003100002 23.4 589 G17003100003 24.3 867 G17003100004 21.5 943 G17003100005 24.1 867 G17003100006 24.4 697 G17003100007 25.6 701 County ID Mean Ann. Temp. Max. Ann. Precip. Rent, Rural Rent, Urban Own, Rural Own, Urban G17003100001 21.2 768 3129 1063 637 365 G17003100002 23.4 589 2949 1075 1469 717 G17003100003 24.3 867 3418 1589 1108 617 G17003100004 21.5 943 1882 425 202 142 G17003100005 24.1 867 2416 572 426 197 G17003100006 24.4 697 2560 934 950 563 G17003100007 25.6 701 2126 653 321 215 characteristics for administrative districts
  • 11. Location-Based Integration Rasters of population and environment data Microdata Area-level dataRasters
  • 13. Collection Expansion  Add more census/survey data  Add more global environmental data  Add more GIS mapping files  Develop data curation protocol(s) for adding additional data to TerraPop  Develop mechanisms for scholars to deposit data/metadata into TerraPop  Allow others’ data to be integrated with other TerraPop data
  • 14. Upcoming Activities  Beta system public release – soon!  User interface redesign for Fall 2014  Conference workshops  IASSIST – Toronto – June 3, 2014  Population Association of America – Boston – April 30, 2014  More to come in last 2014/early 2015  Become a DataONE member node  Continue working with SEAD and DFC on potential collaborations
  • 15. Keep in touch with TerraPop -Website: http://www.terrapop.org -Data access system: http://beta.terrapop.org -Twitter: @TerraPopulus -Email: David Van Riper – vanriper@umn.edu

Editor's Notes

  • #9: Integration across domains, formats hinges on geographyUsers get any type of data in format useful to themRequires boundary files, boundaries harmonized over time
  • #10: Integration across domains, formats hinges on geographyUsers get any type of data in format useful to themRequires boundary files, boundaries harmonized over time
  • #11: Integration across domains, formats hinges on geographyUsers get any type of data in format useful to themRequires boundary files, boundaries harmonized over time
  • #12: Integration across domains, formats hinges on geographyUsers get any type of data in format useful to themRequires boundary files, boundaries harmonized over time