IPUMS-Terra: integrated big heterogeneous spatiotemporal data analysis system

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3 Scopus citations

Abstract

Big Geo Data promises tremendous benefits to the GIS Science community in particular and the broader scientific community in general, but has been primarily of use to the relatively small body of GIScientists who possess the specialized knowledge and methods necessary for working with this class of data. Much of the greater scientific community is not equipped with the expert knowledge and techniques necessary to fully take advantage of the promise of big spatial data. IPUMS-Terra provides integrated spatiotemporal data to these scholars by simplifying access to thousands of raster and vector datasets, integrating them and providing them in formats that are useable to a broad array of research disciplines. IPUMS-Terra exemplifies a new class of National Spatial Data Infrastructure because it connects a large spatial data repository to advanced computational resources, allowing users to access the needle of information they need from the haystack of big spatial data. The project is trailblazing in its commitment to the open sharing of spatial data and spatial tool development, including describing its architecture, process development workflows, and openly sharing its products for the general use of the scientific community.

Original languageEnglish (US)
Pages (from-to)343-361
Number of pages19
JournalJournal of Geographical Systems
Volume20
Issue number4
DOIs
StatePublished - Oct 1 2018

Bibliographical note

Funding Information:
We would like to thank the editor and peer reviewers for providing feedback on this article. Additionally, we would like to thank members of the Institute of Social Research and Data Innovation and the data project teams IPUMS-I and IPUMS-Terra for their help in this process. Special thanks to the IT-Core for assisting with this development process. The research in this article is supported by National Institutes of Health Award 5T32CA163184.

Funding Information:
Acknowledgements We would like to thank the editor and peer reviewers for providing feedback on this article. Additionally, we would like to thank members of the Institute of Social Research and Data Innovation and the data project teams IPUMS-I and IPUMS-Terra for their help in this process. Special thanks to the IT-Core for assisting with this development process. The research in this article is supported by National Institutes of Health Award 5T32CA163184.

Publisher Copyright:
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • IPUMS-Terra
  • Spatial data infrastructure
  • Spatial–temporal data
  • Spatiotemporal analysis

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