Cross-organizational data quality and semantic integrity
Subtitle: learning and reasoning about data semantics with context interchange mediation
By: Allen Mounton, Stuart E. Madnick, and Michael D. Siegel.
Contributors: Madnick, Stuart E.; Siegel, Michael D.; Sloan School of Management.; Center for eBusiness@MIT.
Series: eBusiness@MIT working paper -- 108; Sloan working paper -- 4183-01; Working paper (Sloan School of Management) -- 4183.
Publisher: MIT Sloan School of Management
Published: 2001
Place of publication: [Cambridge, Mass.]
Language: eng
Subjects: Electronic commerce.
Description: 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.