Principles of distributed database systems
Principles of distributed database systems
Comparison of Schema Matching Evaluations
Revised Papers from the NODe 2002 Web and Database-Related Workshops on Web, Web-Services, and Database Systems
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Rondo: a programming platform for generic model management
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
iMAP: discovering complex semantic matches between database schemas
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
eTuner: tuning schema matching software using synthetic scenarios
The VLDB Journal — The International Journal on Very Large Data Bases
Matching large schemas: Approaches and evaluation
Information Systems
Model management 2.0: manipulating richer mappings
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
XBenchMatch: a benchmark for XML schema matching tools
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Schema mapping verification: the spicy way
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
STBenchmark: towards a benchmark for mapping systems
Proceedings of the VLDB Endowment
Clio: Schema Mapping Creation and Data Exchange
Conceptual Modeling: Foundations and Applications
Schema mapping and query translation in heterogeneous P2P XML databases
The VLDB Journal — The International Journal on Very Large Data Bases
OpenII: an open source information integration toolkit
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Beauty and the beast: the theory and practice of information integration
ICDT'07 Proceedings of the 11th international conference on Database Theory
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Schema matching algorithms aim to identify relationships between database schemas, which are useful in many data integration tasks. However, the results of most matching algorithms are expressed as semantically inexpressive, 1-to-1 associations between pairs of attributes or entities, rather than semantically-rich characterisations of relationships. This paper presents a benchmark for evaluating schema matching algorithms in terms of their semantic expressiveness. The definition of such semantics is based on the classification of schematic heterogeneities of Kim et al.. The benchmark explores the extent to which matching algorithms are effective at diagnosing schematic heterogeneities. The paper contributes: (i) a wide range of scenarios that are designed to systematically cover several reconcilable types of schematic heterogeneities; (ii) a collection of experiments over the scenarios that can be used to investigate the effectiveness of different matching algorithms; and (iii) an application of the experiments for the evaluation of matchers from three well-known and publicly available schema matching systems, namely COMA++, Similarity Flooding and Harmony.