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Representation and Reasoning about Changing Semantics in Heterogeneous Data Sources



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Representation and Reasoning about Changing Semantics in Heterogeneous Data Sources SWDB VLDB Hongwei Zhu Stuart E Madnick Michael D Siegel Working Paper CISL 2004 14 August 2004 Composite Information Systems Laboratory CISL Sloan School of Management Room E53 320 Massachusetts Institute of Technology Cambridge MA 02142 Representation and Reasoning about Changing Semantics in Heterogeneous Data Sources Hongwei Zhu Stuart E Madnick Michael D Siegel MIT Sloan School of Management 30 Wadsworth Street MA 02142 USA mrzhu smadnick msiegel mit edu http interchange mit edu coin Abstract Changes of semantics in data sources further complicate the semantic heterogeneity problem We identify four types of semantic heterogeneities related to changing semantics and present a solution based on an extension to the Context Interchange COIN framework Changing semantics is represented as multi valued contextual attributes in a shared ontology however only a single value is valid over a certain time interval A mediator implemented in abductive constraint logic programming processes the semantics by solving temporal constraints for single valued time intervals and automatically applying conversions to resolve semantic differences over these intervals We also discuss the scalability of the approach and its applicability to the Semantic Web 1 Introduction The Web has become a large database from which obtaining meaningful data is becoming increasingly difficult As a simple example try querying historic stock prices for Daimler Benz from Yahoo Figure 1 shows what Yahoo returned for the prices at stock exchanges in New York and Frankfurt Fig 1 Stock prices for Daimler Chrysler from Yahoo Top New York Bottom Frankfurt What conclusions will you draw from the retrieved data Perhaps you regret that you were not arbitraging the substantial price differences between the exchanges or feel lucky that you sold the stock in your Frankfurt account at the end of 1998 Both conclusions are wrong Here not



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