HR: 1340h
AN: IN43A-0319    [Abstracts]
TI: Knowledge Representation in Support of Data Discovery, Access, and Retrieval
AU: * Immer, E
EM: Lis.Immer@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Daley, R
EM: Rose.Daley@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Weiss, M
EM: Michele.Weiss@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Hashemian, M
EM: Mohammad.Hashemian@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Morrison, D
EM: Danny.Morrison@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Fortner, B
EM: Brand.Fortner@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Jen, J
EM: Julia.Jen@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AU: Holder, R
EM: Robert.Holder@jhuapl.edu
AF: JHU/APL, 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AB: Knowledge representation is an increasingly important and complex component in the development of new computer systems that are designed to integrate a variety of diverse data resources for cross-discipline scientific investigation. In particular, a descriptive and intuitive model of the scientific domain is critical to provide enough overall understanding to Earth and Space scientists so they may comfortably work in the domain, and to computer scientists so they may build systems in support of the science missions. Furthermore, a detailed representation of the available data resources specifying their access and use must be available to integrate data discovery and retrieval into such systems. At the Johns Hopkins University Applied Physics Laboratory, we have developed a prototype system (called SRAS - the Scientific Resource Access System) as a testbed to research and develop approaches to resolving some of the difficult knowledge representation problems such as (1) terminology variations across scientific disciplines, (2) differing levels of detail between data resources, and (3) integrating capabilities with existing data systems. We will present an overview of approaches to these and other knowledge representation challenges.
DE: 2799 General or miscellaneous
DE: 7599 General or miscellaneous
DE: 7999 General or miscellaneous
DE: 9810 New fields (not classifiable under other headings)
DE: 9820 Techniques applicable in three or more fields
SC: Earth and Space Science Informatics [IN]
MN: Fall Meeting 2005