Exploring schema similarity at multiple resolutions

  • Authors:

  • Ken Smith;Craig Bonaceto;Chris Wolf;Beth Yost;Michael Morse;Peter Mork;Doug Burdick

  • Affiliations:

  • The MITRE Corporation, McLean, VA, USA;The MITRE Corporation, Bedford, MA, USA;The MITRE Corporation, McLean, VA, USA;The MITRE Corporation, Bedford, MA, USA;The MITRE Corporation, McLean, VA, USA;The MITRE Corporation, McLean, VA, USA;The MITRE Corporation, McLean, VA, USA

  • Venue:
  • Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
  • Year:
  • 2010

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Abstract

Large, dynamic, and ad-hoc organizations must frequently initiate data integration and sharing efforts with insufficient awareness of how organizational data sources are related. Decision makers need to reason about data model interactions much as they do about data instance interactions in OLAP: at multiple levels of granularity. We demonstrate an integrated environment for exploring schema similarity across multiple resolutions. Users visualize and interact with clusters of related schemas using a tool named Affinity. Within any cluster, users may drill-down to examine the extent and content of schema overlap. Further drill down enables users to explore fine-grained element-level correspondences between between two selected schemas.