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@inproceedings{DBLP:conf/vldb/Madnick95,
author = {Stuart E. Madnick},
editor = {Umeshwar Dayal and
Peter M. D. Gray and
Shojiro Nishio},
title = {From VLDB to VMLDB (Very MANY Large Data Bases): Dealing with
Large-Scale Semantic Heterogenity},
booktitle = {VLDB'95, Proceedings of 21th International Conference on Very
Large Data Bases, September 11-15, 1995, Zurich, Switzerland},
publisher = {Morgan Kaufmann},
year = {1995},
isbn = {1-55860-379-4},
pages = {11-16},
ee = {db/conf/vldb/Madnick95.html},
crossref = {DBLP:conf/vldb/95},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
The popularity of distributed computing environments and the growth of the"Information SuperHighway" have dramatically increased the number of data bases available for use. Unfortunately, there are significant challenges to be overcome.
One particular problem is context interchange, whereby each source of information and potential receiver of that information may operate witha different context, leading to large- scale semantic heterogeneity. A context is the collection of implicit assumptions about the context definition (i.e., meaning) and context characteristics (i.e., quality) of the information. This paper describes various forms of context challenges and examples of potential context mediation services, such as data semantics acquisition, data quality attributes, and evolving semantics and quality, that can mitigate the problem.
Copyright © 1995 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.
