Small Business Innovation Research/Small Business Tech Transfer
Automated Semantic Enrichment for Data Discovery and Decision Support
Project Description
The objective of this proposal is to demonstrate a set of methods for automatically extracting metadata from diverse data sets to serve as a common vocabulary by which data can easily be queried, retrieved and combined for visualization in a geobrowser. We propose extracting keyword tags from both structured and unstructured data sets by applying natural language processing (NLP) to metadata and unstructured content. The extracted tags will be associated with each data set as supplementary metadata to assist with data discovery, categorization and spatial-temporal location. We combine manually-generated tags, based on domains of interest or specific decision support activities, with automatically generated tags from NLP, and to develop hierarchical clusters of the combined tags to serve as a common set of descriptors by which different data sets can be discovered and combined. If proven successful, our approach will be useful for the management and fusion of very large and diverse data sets not only for applied science and decision support, but also for emergency management and related security operations, for business intelligence, and for other application involving large quantities of diverse data, both structured and unstructured.
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Anticipated Benefits
The proposed technology is of general use for diverse data set integration into existing NASA-sponsored, applied science and decision support programs, such as water management decision support (e.g. BASINS, AWARDS, and NWS RFS), natural disaster applications (e.g. Global Flood and Landslide Monitoring and Prediction; WRAP), and ecological forecasting applications (e.g. NPS Resource Management; Fire Information for Resource Management System).
Targeted industries include the following: emergency management, infrastructure security (principally with DHS), business intelligence, natural resource and environmental management, and other land use and infrastructure applications. For Emergency Management, a principal customer/proponent likely is DHS, however state and local government agencies would benefit from a cost effective means of fusing data and integrating with federal agencies for emergency management. For federal government agency opportunities in security and battlespace awareness, geoVisual intends to leverage any SBIR-sponsored programs, such as Navy TAP, for meeting with and demonstrating to, large systems integrators like Boeing, Raytheon or Lockheed Martin. For business intelligence applications, large firms involved in data mining and business analytics solutions are the best candidate customers. More »
Targeted industries include the following: emergency management, infrastructure security (principally with DHS), business intelligence, natural resource and environmental management, and other land use and infrastructure applications. For Emergency Management, a principal customer/proponent likely is DHS, however state and local government agencies would benefit from a cost effective means of fusing data and integrating with federal agencies for emergency management. For federal government agency opportunities in security and battlespace awareness, geoVisual intends to leverage any SBIR-sponsored programs, such as Navy TAP, for meeting with and demonstrating to, large systems integrators like Boeing, Raytheon or Lockheed Martin. For business intelligence applications, large firms involved in data mining and business analytics solutions are the best candidate customers. More »
Primary U.S. Work Locations and Key Partners
| Organizations Performing Work | Role | Type | Location |
|---|---|---|---|
| GeoVisual Technologies, Inc. | Lead Organization | Industry | Boulder, Colorado |
Stennis Space Center
(SSC)
|
Supporting Organization | NASA Center | Stennis Space Center, Mississippi |
Primary U.S. Work Locations
-
Colorado
-
Mississippi
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This is a historic project that was completed before the creation of TechPort on October 1, 2012. Available data has been included. This record may contain less data than currently active projects.