CyberGIS-poster-si2-Feb2017-Wangetal.pdf

2017-02-19T16:49:37Z (GMT) by Shaowen Wang
Originally developed by geographers in the mid-1960s, Geographic Information Systems (GIS) have flourished since that time. In the foreseeable future, GIS software will continue to play essential roles for breaking through scientific challenges in numerous fields and improving decision-making practices with broad societal impacts. However, fulfilling such roles is increasingly dependent on the ability to handle very large spatiotemporal data sets and complex analysis software based on synthesizing computational and spatial thinking enabled by cyberinfrastructure, which conventional GIS-based software approaches do not provide. This project will establish CyberGIS as a fundamentally new software framework comprising a seamless integration of cyberinfrastructure, GIS, and spatial analysis/modeling capabilities. Specifically, the project will: 1) engage a multidisciplinary community through a participatory approach in evolving CyberGIS software requirements; 2) integrate and sustain a core set of composable, interoperable, manageable, and reusable CyberGIS software elements based on community-driven and open source strategies; 3) empower high-performance and scalable CyberGIS by exploiting spatial characteristics of data and analytical operations for achieving unprecedented capabilities for geospatial knowledge discovery; 4) enhance an online geospatial problem solving environment to allow for the contribution, sharing, and learning of CyberGIS software by numerous users, which fosters the development of education, outreach, and training programs crosscutting multiple disciplines; 5) deploy and test CyberGIS software by linking with national and international cyberinfrastructure to achieve scalability to significant sizes of geospatial problems, cyberinfrastructure resources, and user communities; and 6) evaluate and improve the CyberGIS framework through domain science applications and vibrant partnerships to gain better understanding of the complexity of coupled human-natural systems.