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Mappings between disparate models are fundamental to any application that requires interoperability between heteroge-neous data and applications. Generating mappings is a labor-intensive and error prone task. To build a system that helps users generate mappings, we need an explicit representation of mappings. This representation needs to have well-defined semantics to enable reasoning and comparison between map-pings. This paper first presents a powerful framework for defining languages for specifying mappings and their associ-ated semantics. We examine the use of mappings and identify the key inference problems associated with mappings. These properties can be used to determine whether a mapping is ad-equate in a particular context. Finally, we consider an in-stance of our framework for a language representing map-pings between relational data. We present sound and com-plete algorithms for the corresponding inference problems. 1
Madhavan et al. (Sun,) studied this question.