Cross-Organizational Data Quality and Semantic Integrity: Learning and Reasoning About Data Semantics with Context Interchange Mediation

4 Pages Posted: 14 Nov 2001

See all articles by Allen Moulton

Allen Moulton

Massachusetts Institute of Technology (MIT)

Stuart Madnick

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Michael Siegel

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: October 2001

Abstract

We use a context interchange mediation approach for detecting and resolving data quality and semantic integrity conflicts in information exchanged across organizational boundaries. Context models draw on a domain ontology to explain how source and receiver data models implement general principles of the subject domain. Using the declarative knowledge from the domain ontology and context models, the mediator writes a query plan meeting receiver semantic requirements from autonomous, heterogeneous sources. Examples drawn from fixed income securities investments illustrate problems and solutions enabled by context interchange mediation.

Suggested Citation

Moulton, Allen and Madnick, Stuart E. and Siegel, Michael, Cross-Organizational Data Quality and Semantic Integrity: Learning and Reasoning About Data Semantics with Context Interchange Mediation (October 2001). Available at SSRN: https://ssrn.com/abstract=289992 or http://dx.doi.org/10.2139/ssrn.289992

Allen Moulton

Massachusetts Institute of Technology (MIT) ( email )

Center of International Studies
Cambridge, MA 02139
United States

Stuart E. Madnick (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

E53-321
Cambridge, MA 02142
United States
617-253-6671 (Phone)
617-253-3321 (Fax)

Michael Siegel

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

E53-323
Cambridge, MA 02142
United States
617-253-2937 (Phone)
617-258-7579 (Fax)

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