CHS: Small: The Future of Geospatial Data: The Analytics and Implications of Open Source Mapping

University Of Colorado At Boulder, Boulder CO

Investigators

Abstract

This project will produce methods and tools in the critical area of geospatial data that both the larger computer science research community can use as well as the public-sector and private-sector development communities. Geospatial data are a critical area of research and development, notably in supporting rapid response to disasters arising from natural or technological hazards, as well as other sudden crises. This research will deeply investigate the conditions under which volunteer-generated data in "open source mapping" environments are generated and used. The tools developed in this project will help further validate volunteer-generated open geospatial data, and enable appropriate use through better analytical inspection methods. In addition, the connections between social computing activities and impacts on the world will be substantiated in clear ways, especially through the windows of humanitarian events and societal resilience-building. How open mapping can be made more viable for social problems will also be advanced through this research. To achieve these goals, the team will design, develop, deploy, and evaluate a software infrastructure and its associated application programming interface that operates on large historical files of OpenStreetMap data. OpenStreetMap is a 2+ million member, decade-old volunteer-based organization that has created a "open data" based digital map of the world. This research will allow examination of the interpersonal, group, and organizational means by which collaborative cartography is accomplished through social computing. It will then examine the implications of having open geospatial data available to humanitarian efforts, which are important drivers to socio-technical change, including that of disaster response, resilience-building of critical infrastructure, and other governmental responsibilities. The research combines computational and behavioral analytics to address critical questions at multiple levels of analysis, from database instantiation to institutional use.