JPL Technical Report Server

Smarter Earth Science Data System

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dc.contributor.author Huang, Thomas
dc.date.accessioned 2013-11-11T15:19:23Z
dc.date.available 2013-11-11T15:19:23Z
dc.date.issued 2013-09-19
dc.identifier.citation 5th International Conference on Knowledge Engineering and Ontology Development, Algarve, Portugal, September 19, 2013. en_US
dc.identifier.clearanceno 13-1428
dc.identifier.uri http://hdl.handle.net/2014/43965
dc.description.abstract The explosive growth in Earth observational data in the recent decade demands a better method of interoperability across heterogeneous systems. The Earth science data system community has mastered the art in storing large volume of observational data, but it is still unclear how this traditional method scale over time as we are entering the age of Big Data. Indexed search solutions such as Apache Solr (Smiley and Pugh, 2011) provides fast, scalable search via keyword or phases without any reasoning or inference. The modern search solutions such as Googles Knowledge Graph (Singhal, 2012) and Microsoft Bing, all utilize semantic reasoning to improve its accuracy in searches. The Earth science user community is demanding for an intelligent solution to help them finding the right data for their researches. The Ontological System for Context Artifacts and Resources (OSCAR) (Huang et al., 2012), was created in response to the DARPA Adaptive Vehicle Make (AVM) programs need for an intelligent context models management system to empower its terrain simulation subsystem. The core component of OSCAR is the Environmental Context Ontology (ECO) is built using the Semantic Web for Earth and Environmental Terminology (SWEET) (Raskin and Pan, 2005). This paper presents the current data archival methodology within a NASA Earth science data centers and discuss using semantic web to improve the way we capture and serve data to our users. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en en_US
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2013. en_US
dc.subject semantic web en_US
dc.subject data center en_US
dc.subject reasoning en_US
dc.title Smarter Earth Science Data System en_US
dc.type Preprint en_US


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