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A Model for Semantic Equivalence Discovery for Harmonizing Master Data

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5872))

Abstract

IT projects often face the challenge of harmonizing metadata and data so as to have a “single” version of the truth. Determining equivalency of multiple data instances against the given type, or set of types, is mandatory in establishing master data legitimacy in a data set that contains multiple incarnations of instances belonging to the same semantic data record . The results of a real-life application define how measuring criteria and equivalence path determination were established via a set of “probes” in conjunction with a score-card approach. There is a need for a suite of supporting models to help determine master data equivalency towards entity resolution—including mapping models, transform models, selection models, match models, an audit and control model, a scorecard model, a rating model. An ORM schema defines the set of supporting models along with their incarnation into an attribute based model as implemented in an RDBMS.

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© 2009 Springer-Verlag Berlin Heidelberg

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Piprani, B. (2009). A Model for Semantic Equivalence Discovery for Harmonizing Master Data. In: Meersman, R., Herrero, P., Dillon, T. (eds) On the Move to Meaningful Internet Systems: OTM 2009 Workshops. OTM 2009. Lecture Notes in Computer Science, vol 5872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05290-3_81

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  • DOI: https://doi.org/10.1007/978-3-642-05290-3_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05289-7

  • Online ISBN: 978-3-642-05290-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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