A survey of approaches to automatic schema matching

@article{rahm_01_survey, abstract = {Abstract. Schema matching is a basic problem in many database application domains, such as data integration, Ebusiness, data warehousing, and semanticquery processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.}, author = {Rahm, Erhard and Bernstein, Philip A. }, citeseerurl = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.700}, citeulike-article-id = {2998601}, journal = {VLDB Journal}, number = {10}, pages = {200--1}, posted-at = {2008-07-14 11:57:15}, priority = {2}, title = {A survey of approaches to automatic schema matching}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.700}, volume = {10}, year = {2001} }

TY - JOUR ID - rahm_01_survey L3 - citeulike-article-id:2998601 TI - A survey of approaches to automatic schema matching JF - VLDB Journal VL - 10 IS - 10 SP - 200 EP - 1 N2 - Abstract. Schema matching is a basic problem in many database application domains, such as data integration, Ebusiness, data warehousing, and semanticquery processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component. AU - Rahm, Erhard AU - Bernstein, Philip PY - 2001/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.700 ER -