Querying Heterogeneous Information Sources Using Source Descriptions


We witness a rapid increase in the number of structured information sources that are available online, especially on the WWW. These sources include commercial databases on product information, stock market information, real estate, automobiles, and entertainment. We would like to use the data stored in these databases to answer complex queries that go beyond keyword searches. We face the following challenges: (1) Several information sources store interrelated data, and any query-answering system must understand the relationships between their contents. (2) Many sources are not full-featured database systems and can answer only a small set of queries over their data (for example, forms on the WWW restrict the set of queries one can ask). (3) Since the number of sources is very large, e ective techniques are needed to prune the set of information sources accessed to answer a query. (4) The details of interacting with each source vary greatly. We describe the Information Manifold, an implemented system that provides uniform access to a heterogeneous collection of more than 100 information sources, many of them on the WWW. IM tackles the above problems by providing a mechanism to describe declaratively the contents and query capabilities of available information sources. There is a clean separation between the declarative source description and the actual details of interacting with an information source. We describe algorithms that use the source descriptions to prune e ciently the set of information sources for a given query and practical algorithms to generate executable query plans. The query plans we generate can involve querying several information sources and combining their answers. We also present experimental studies that indicate that the architecture and algorithms used in the Information Manifold scale up well to several hundred information sources.

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@inproceedings{Halevy1996QueryingHI, title={Querying Heterogeneous Information Sources Using Source Descriptions}, author={Alon Y. Halevy and Anand Rajaraman and Joann J. Ordille}, booktitle={VLDB}, year={1996} }