Using known schemas and mappings to construct new semantic mappings

This dissertation studies the problem of constructing semantic mappings, i.e., expressions that relate different schemas. Semantic mappings play an important role in modern information systems. They let applications relate data in different sources and thus enable them to fruitfully leverage information residing in various forms across multiple data sources. With the proliferation of information systems that adopt distributed and often heterogeneous architectures, there is a need for automated support and tools to better facilitate the construction of semantic mappings. Our thesis is that, given a mapping construction task, knowledge that exists in other schemas and previously known mappings related to the mapping task, can be exploited to construct the required mapping. Our hypothesis is based on the two intuitions that mapping construction tasks are often repetitive in nature, and that different schemas within a domain are alternate representations for the same underlying entities. We demonstrate this in the context of two problems that are crucial to mapping construction. First, we address the problem of schema matching, i.e., the problem of identifying semantically similar elements in different schemas. We first describe techniques to match schemas elements based on their names, data instances, relationships with other elements, and known desirable properties of mappings. Then, given a new mapping task, we describe different ways in which known schemas and mappings within the same domain can be used to enhance the matching performance of a conventional schema matcher. Our approach is called corpus-based matching and our experimental results demonstrate its improved performance over direct matching techniques. Second, we address the problem of mapping composition, i.e., the problem of constructing a direct mapping between two schemas from existing mappings to a common schema. We show that, the composition problem can have very surprising consequences in the case of commonly used GLAV mappings. Specifically, the composition of mappings with finite formulas can in fact have infinite formulas. We further describe how and when compositions, even when infinite, can be encoded in a finite representation. Finally, we show how known query answering algorithms can be extended to handle compositions with infinite formulas.