Intelligent Archiving and Physics Mining of Large Data Sets (Invited)

Details Intelligent Archiving and Physics Mining of Large Data Sets (Invited) Intelligent Archiving and Physics Mining of Large Data Sets (Invited)

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsm51b..01k&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #SM51B-01

Physics

[1914] Informatics / Data Mining, [1974] Informatics / Social Networks, [1996] Informatics / Web Services, [2794] Magnetospheric Physics / Instruments And Techniques

Scientific paper

There are unique challenges in all aspects related to large data sets, from storage, search and access, to analysis and file sharing. With few exceptions, the adoption of the latest technologies to deal with the management and mining of large data sets has been slow in heliosciences. Web services such as CDAweb have been very successful and have been widely adopted by the community. There are also significant efforts going towards Virtual Observatories (VxOs). The main thrust of VxOs has so far been on data discovery, aggregation and uniform presentation. While work remains, many VxOs can now be used to access data. However data is not knowledge and the challenge of extracting physics from the large data sets remains. Here we review our efforts on (i) implementing advanced data mining techniques as part of the data-to-knowledge discovery pipeline, and (ii) use of social networking paradigm in the development of a science collaboratory environment that enables sharing of large files, creation of projects, among others. We will present new data mining software that works on a variety of data formats and demonstrate its capability through several examples of analysis of spacecraft data. The use of such techniques in intelligent archiving will be discussed. Finally, the use of our science collaboratory service and its unique sharing features such as universal accessibility of staged files will be illustrated.

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