Overview
Visualizations of geographically-referenced data, such as measures of disease occurrence across the country or atmospheric data around the globe, can be immensely useful. But developing applications using such datasets can be immensely challenging. There is no standard format or cataloging system for geo-referenced data, and once the datasets are found and formatted, they must then be merged with an appropriate mapping system for visualization.
RENCI and others have garnered broad experience in developing infrastructures to work with and deliver geospatial data, but this work has largely been achieved on an ad-hoc basis, resulting in systems that function well, but separately. These emergent infrastructures offer opportunities for reuse, integration, and extension by taking the best components and lessons learned from each project and combining and extending them into a single innovative cyberinfrastructure for geospatial data.
RENCI’s Geoanalytics Framework will allow for Web-based display, analysis and curation of geo-referenced data. This initiative seeks to make geo-referenced data more accessible for researchers and practitioners who are not trained in the science of geographic information systems, and to provide a common platform for data analysis and insight. Once completed, the platform will be made available as an open resource to university centers, institutes and departments and other stakeholders for customization and continued use.
Overview
Visualizations of geographically-referenced data, such as measures of disease occurrence across the country or atmospheric data around the globe, can be immensely useful. But developing applications using such datasets can be immensely challenging. There is no standard format or cataloging system for geo-referenced data, and once the datasets are found and formatted, they must then be merged with an appropriate mapping system for visualization.
RENCI and others have garnered broad experience in developing infrastructures to work with and deliver geospatial data, but this work has largely been achieved on an ad-hoc basis, resulting in systems that function well, but separately. These emergent infrastructures offer opportunities for reuse, integration, and extension by taking the best components and lessons learned from each project and combining and extending them into a single innovative cyberinfrastructure for geospatial data.
RENCI’s Geoanalytics Framework will allow for Web-based display, analysis and curation of geo-referenced data. This initiative seeks to make geo-referenced data more accessible for researchers and practitioners who are not trained in the science of geographic information systems, and to provide a common platform for data analysis and insight. Once completed, the platform will be made available as an open resource to university centers, institutes and departments and other stakeholders for customization and continued use.
Funding
National Weather Service
Project Team
Jeff Heard, project lead
Ken Gallupi
Ray Idaszak
David Knowles
John McGee
Charles Schmitt
