ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4/W2, 95-102, 2015
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/95/2015/
doi:10.5194/isprsannals-II-4-W2-95-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
10 Jul 2015
WORLD SPATIOTEMPORAL ANALYTICS AND MAPPING PROJECT (WSTAMP): DISCOVERING, EXPLORING, AND MAPPING SPATIOTEMPORAL PATTERNS ACROSS THE WORLD’S LARGEST OPEN SORUCE DATA SETS
R. Stewart1, J. Piburn2, A. Sorokine1, A. Myers1, J. Moehl2, and D. White1 1Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831, USA
2Oak Ridge Associated Universities, 1 Bethel Valley Road, Oak Ridge, TN 37831, USA
Keywords: Global, Data Mining, Spatiotemporal, Visualization, Tool, Analytics Abstract. The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, and changing attributes, as well as content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 10,000+ attributes covering over 200 nation states spanning over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We discuss the status of this work and report on major findings.
Conference paper (PDF, 1315 KB)


Citation: Stewart, R., Piburn, J., Sorokine, A., Myers, A., Moehl, J., and White, D.: WORLD SPATIOTEMPORAL ANALYTICS AND MAPPING PROJECT (WSTAMP): DISCOVERING, EXPLORING, AND MAPPING SPATIOTEMPORAL PATTERNS ACROSS THE WORLD’S LARGEST OPEN SORUCE DATA SETS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4/W2, 95-102, doi:10.5194/isprsannals-II-4-W2-95-2015, 2015.

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