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NASA's mission is to pioneer the future in space exploration, scientific discovery and aeronautics research.

To do that, thousands of people have been working around the world -- and off of it -- for 50 years, trying to answer some basic questions. What's out there in space? How do we get there? What will we find? What can we learn there, or learn just by trying to get there, that will make life better here on Earth?

Sponsored Projects:

TW LogoData Quality Screening Service (DQSS)
Co Investigator: Peter Fox
Description: Objective Make data quality information easy to use for the water cycle community Expert and non-specialist users alike Human and machine users alike Connect users seamlessly to best practices in data quality handling, i.e., the science team recommendations for quality screening (filtering) Enable higher and more correct utilization of data quality indicators in data analysis
TW LogoScientific Knowledge Integration Framework (SKIF)
Principal Investigator: Peter Fox
Description: The overall goal of this effort is to bring together key aspects of intelligent systems, namely data mining / knowledge extraction and semantic knowledge representation, and to prove the benefit of this approach by applying it to a science problem that is representative of NASA Science Mission Directorate research interests.
TW LogoSemantically-Enabled Science Data Integration (SESDI)
Principal Investigator: Peter Fox
Description: The vast majority of explorations of the Earth system are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. In many cases, syntax-only interoperability IS the state-of-the-art. In order for scientists and non-scientists to discover, access, and use data from unfamiliar sources, they are forced to learn details of the data schema, other people¿s naming schemes and syntax decisions. Our work is aimed at providing scientists with the option of describing what they are looking for in terms that are meaningful and natural to them, instead of in a syntax that is not. The missing element in enabling the higher-level interconnections is the technology of ontologies, ontology-equipped tools, and semantically aware interfaces between science components. Ontologies fill a major technology gap in machine-to-machine communication across multiple disciplines to advance Earth system science by enabling data integration without the need for human intervention. This project, the Semantically-Enabled Science Data Integration (SESDI), will demonstrate how ontologies implemented within existing distributed technology frameworks will provide essential, re-useable, and robust, support for an evolution to science measurement processing systems (or frameworks) as well as for data and information systems (or framework) support for NASA Science Focus Areas and Applications.