Schema Evolution publication categorizer

Schema mapping techniques for data exchange have become popular and useful tools both in research and industry. A schema mapping relates a source schema with a target schema via correspondences, which are specified by a domain expert possibly supported by automated schema matching algorithms. The set of correspondences, i.e., the mapping, is interpreted as a data transformation usually expressed as a query. These queries transform data from the source schema to conform to the target schema. They can be used to materialize data at the target or used as views in a virtually integrated system. We present a classification of mapping situations that can occur when mapping between two relational or nested (XML) schemata. Our classification takes into consideration 1:1 and n:m correspondences, attribute-level and higher-level mappings, and special constructs, such as choice constraints, cardinality constraints, and data types. Based on this classification, we have developed a general suite of schemata, data, and correspondences to test the ability of tools to cope with the different mapping situations. We evaluated several commercial and research tools that support the definition of schema mappings and interpret this mapping as a data transformation. We found that no tool performs well in all mapping situations and that many tools produce incorrect data transformations. The test suite can serve as a benchmark for future improvements and developments of schema mapping tools.