HR: 17:30h
AN: SF34A-07    [Abstracts]
TI: Intelligent Systems Technologies and Utilization of Earth Observation Data
AU: * Ramapriyan, H K
EM: Rama.Ramapriyan@nasa.gov
AF: NASA Goddard Space Flight Center, Code 423, NASA/GSFC, Greenbelt, MD 20771 United States
AU: McConaughy, G
EM: Gail.McConaughy@nasa.gov
AF: NASA Goddard Space Flight Center, Code 586, NASA/GSFC, Greenbelt, MD 20771 United States
AU: Lynnes, C
EM: Christopher.S.Lynnes@nasa.gov
AF: NASA Goddard Space Flight Center, Code 902, NASA/GSFC, Greenbelt, MD 20771 United States
AU: Morse, S
EM: smorse@sosacorp.com
AF: SoSA Corporation, 14900 Conference Center Drive, Suite 375, Chantilly, VA 20151 United States
AU: Isaac, D
EM: david.isaac@teambps.com
AF: Business Performance Systems, 7808 Trevino Lane, Falls Church, VA 22043 United States
AB: The last decade's influx of raw data and derived geophysical parameters from several Earth observing satellites to NASA data centers has created a data-rich environment for Earth science research and applications. For example, the Distributed Active Archive Centers of NASA's Earth Observing System Data and Information System held over 2.8 petabytes of data at the end of 2003, growing at a rate of about 3 terabytes per day. The data products are distributed to a large community of scientific researchers, educators and operational government agencies. With advances in computational hardware, networks, information management and software technologies, much progress has been made over the last decade in data archiving and providing data access for a broad, diverse user community. However, to realize the full potential of the growing archives of valuable scientific data, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. The set of providers of data and services pertaining to archiving and distribution of Earth science data is quite heterogeneous and distributed today and is likely to be even more so in the future. This is due to the diversity of Earth Science disciplines and the distribution of expertise needed to provide data and services in those disciplines. Thus, in typical real world applications scenarios, the data and services will be obtained through service chains involving multiple data archive sites or systems. It is in this context that the development of technologies to improve data utilization must occur. Sponsored by NASA's Intelligent Systems Project within the Computing, Information and Communication Technology Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization by adding intelligence into the archives in the context of an overall knowledge building system. Potential Intelligent Archive concepts include: - Mining archived data holdings using Intelligent Data Understanding algorithms to improve metadata to facilitate data access and usability - Building intelligence about transformations on data, information, knowledge, and accompanying services involved in a scientific enterprise - Recognizing the value of results, indexing and formatting them for easy access, and delivering them to concerned individuals - Interacting as a cooperative node in a web of distributed systems to perform knowledge building (i.e., transformations from data to information to knowledge) instead of just data pipelining - Being aware of other nodes in the knowledge building system, participating in open systems interfaces and protocols for virtualization, and collaborative interoperability Some issues we present are: scalability of algorithms that involve intelligent data understanding to enable mining of large data holdings and improve metadata; automated discovery of datasets appropriate to a given application and ingesting them automatically into the users' computational environment; automated quality assessment to facilitate ensuring data quality in large distributed archives; and performance optimization in intelligent archives.
UR: http://daac.gsfc.nasa.gov/IDA/
DE: 9820 Techniques applicable in three or more fields
DE: 6339 System design
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting