TRAMP: Understanding the Behavior of Schema Mappings through Provenance

نویسندگان

  • Boris Glavic
  • Gustavo Alonso
  • Renée J. Miller
  • Laura M. Haas
چکیده

Though partially automated, developing schema mappings remains a complex and potentially error-prone task. In this paper, we present TRAMP (TRAnsformationMapping Provenance), an extensive suite of tools supporting the debugging and tracing of schema mappings and transformation queries. TRAMP combines and extends data provenance with two novel notions, transformation provenance and mapping provenance, to explain the relationship between transformed data and those transformations and mappings that produced that data. In addition we provide query support for transformations, data, and all forms of provenance. We formally define transformation and mapping provenance, present an efficient implementation of both forms of provenance, and evaluate the resulting system through extensive experiments.

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عنوان ژورنال:
  • PVLDB

دوره 3  شماره 

صفحات  -

تاریخ انتشار 2010