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Managing distributed heterogeneos information spaces

: Jasnoch, U.; Balfanz, D.; Coors, V.

Zhang, G.:
10th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2000. Proceedings
Wheaton: Econo Printing & Graphics, Inc., 2000
ISBN: 0-9701053-0-4
International Conference on Flexible Automation and Intelligent Manufacturing (FAIM) <10, 2000, College Park/Md.>
Conference Paper
Fraunhofer IGD ()
metadata; data mining; distributed information space

The shift from the production society to the information society is commonly agreed. Today's challenging task is the "management" of - partially already existing - data in terms of administration, evaluation, and examination. Administration embraces all technologies necessary for the storing, retrieving and migrating data within distributed information spaces. Furthermore, these sources do not necessarily belong to a common model, thus increasing the complexity of administering the information space. Working in distributed and heterogeneous information spaces raises the need for new techniques for relating pieces of data and for examining the data. Technologies like data mining must adapt these requirements and must be extended to fit to these environmental requirements. In order to present the concluding information to the end-user, knowledge management among other AI-techniques like fuzzy logic or rule-based systems are used top extract, evaluate and present the data sets requested by the end-user in an appropriate way.