Using Semantic Search and Knowledge Reasoning to Improve the Discovery of Earth Science Records: An Example with the ESIP Semantic Testbed

Kai Liu, Chaowei Yang, Wenwen Li, Zhipeng Gui, Chen Xu and Jizhe Xia
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Kai Liu: George Mason University, Fairfax, VA, USA
Chaowei Yang: George Mason University, Fairfax, VA, USA
Wenwen Li: Arizona State University, Tempe, AZ, USA
Zhipeng Gui: George Mason University, Fairfax, VA, USA
Chen Xu: George Mason University, Fairfax, VA, USA
Jizhe Xia: George Mason University, Fairfax, VA, USA

International Journal of Applied Geospatial Research (IJAGR), 2014, vol. 5, issue 2, 44-58

Abstract: Web resources exploration is increasingly driven by semantic web technologies with automated processing. Earth science communities generate large amounts of datasets described in hundreds of millions of metadata records. It is critical to discover the accurate data from the millions of data records based on the end user's searching intent. However, the big challenge is how to ensure that catalogs and Spatial Web Portals can understand end user's intents. To enable portals effectively ‘understand' the meaning of user's queries and to provide a better searching experience for end users, we collaborated with Earth Science Information Partners (ESIP) to develop such a capability through a semantic Testbed. We implemented a reasoning engine using similarity calculations to facilitate the meaningful discovery of Earth science data and to improve the accuracy of searching results.

Date: 2014
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