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Harnessing the value of spatial dimension in social research infrastructure

Authors: Bing She*, University of Michigan, Trisha Kunst Martinez, University of Michigan
Topics: Geographic Information Science and Systems
Keywords: Social research, geovisual analytics, machine learning, digital asset management
Session Type: Paper
Presentation File: No File Uploaded

With increasing interest in leveraging spatial analysis among social scientists, data archives are gradually improving their platforms to deposit, curate, search and display spatial data. These archives typically accept deposits from diverse research projects with different spatial extents. The platform also needs to adapt its visualization and analysis methods to different types of spatial data. To maximize the value of spatial dimension in social research infrastructure, a data archive needs to support: 1) automatic geotagging from user-deposited files and metadata, 2) online geovisual analytics adaptive to the data characteristics. This research provides an early attempt to automate geotagging and integrate various geovisual analytics functions on selected ICPSR studies. The built prototype is integrated into ICPSR's Digital Asset Management System (DAMS) – Archonnex for spatial data curation, spatial search, and geovisual analytics. Such integration provides a promising direction for promoting spatial methods among social science communities.

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