The Discover framework for domain knowledge supported analysis and interactive visualization of multivariate spatial-temporal data sets

The Discover Framework is a web-based visualization tool built on freeware or freely distributed executables. The Discover Framework includes interactive time-series data plots, a time-evolving map, and a domain-knowledge-supported story board. It is designed to aid scientific and societal understanding of Earth systems. Aligning data in this manner has the capacity for interdisciplinary knowledge discovery and motivates dialogue about system processes that we seek to enhance through anomaly detection. Development has been conducted with the inspiration and assistance of the NSF RCN IS-GEO (Intelligent Systems for Geosciences). In this presentation, two applications are used to illustrate the capabilities and potential of the Discover Framework: DiscoverWater and DiscoverHABs, and DiscoverIModels.

DiscoverWater integrates streamflow, groundwater pumping, groundwater levels, and Palmer drought severity index data sets, currently from an arid region of the High Plains aquifer in western Kansas. DiscoverWater shows how reservoir- and groundwater-supported irrigation has reduced low flows during droughts from 3 ft³/s during the 1950's drought of record to 0.3 ft³/s during more recent, less severe droughts (streamflows are from the USGS Syracuse gage of the Arkansas River). It also shows how a predominantly wet period obscured this effects of irrigation for 20-years, from 1983 to 2003.

DiscoverHABs combines data and model results from Cheney Reservoir outside of Wichita, Kansas. For this application, a scenario feature of the Discover Framework allows users to choose data combinations expertly chosen to reveal how environmental and biogeochemical variables relate to the formation of harmful algal blooms (HABs).

Future anticipated advances include integration of domain knowledge with quantitative analysis methods suitable for the relatively small data sets typical of the problems considered. We also seek to increase data interoperability and compatibility with other scientific tools, such as those available from EarthCube.