A comparative analysis of methodologies for database schema integration
ACM Computing Surveys (CSUR)
Conceptual schema analysis: techniques and applications
ACM Transactions on Database Systems (TODS)
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
THALIA: Test Harness for the Assessment of Legacy Information Integration Approaches
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Ontology Matching
Matching large schemas: Approaches and evaluation
Information Systems
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
XBenchMatch: a benchmark for XML schema matching tools
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
A survey of schema-based matching approaches
Journal on Data Semantics IV
Ontology alignment evaluation initiative: six years of experience
Journal on data semantics XV
MEDI'12 Proceedings of the 2nd international conference on Model and Data Engineering
Towards an information quality approach to enhance query routing processes
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
Assessing the quality of large-scale data standards: A case of XBRL GAAP Taxonomy
Decision Support Systems
Target-driven merging of taxonomies with Atom
Information Systems
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Schema integration is a central task for data integration. Over the years, many tools have been developed to discover correspondences between schemas elements. Some of them produce an integrated schema. However, the schema matching community lacks some metrics which evaluate the quality of an integrated schema. Two measures have been proposed, completeness and minimality. In this paper, we extend these metrics for an expert integrated schema. Then, we complete them by another metric that evaluates the structurality of an integrated schema. These three metrics are finally aggregated to evaluate the proximity between two schemas. These metrics have been implemented as part of a benchmark for evaluating schema matching tools. We finally report experiments results using these metrics over 8 datasets with the most popular schema matching tools which build integrated schemas, namely COMA++ and Similarity Flooding.