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Querying Semistructured Heterogeneous Information

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Journal of Systems Integration

Abstract

Semistructured data has no absolute schema fixed in advance and its structure may be irregular or incomplete. Such data commonly arises in sources that do not impose a rigid structure (such as the World-Wide Web) and when data is combined from several heterogeneous sources. Data models and query languages designed for well structured data are inappropriate in such environments. Starting with a “lightweight” object model adopted for the TSIMMIS project at Stanford, in this paper we describe a query language and object repository designed specifically for semistructured data. Our language provides meaningful query results in cases where conventional models and languages do not: when some data is absent, when data does not have regular structure, when similar concepts are represented using different types, when heterogeneous sets are present, and when object structure is not fully known. This paper motivates the key concepts behind our approach, describes the language through a series of examples (a complete semantics is available in an accompanying technical report [23]), and describes the basic architecture and query processing strategy of the “lightweight” object repository we have developed.

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Authors and Affiliations

  1. Department of Computer Science, Stanford University, Stanford, CA, 94305-2140

    Dallan Quass, Anand Rajaraman, Jeffrey Ullman & Jennifer Widom

  2. Department of Computer Science, Hebrew University, Jerusalem, Israel

    Yehoshua Sagiv

Authors
  1. Dallan Quass
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  2. Anand Rajaraman
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  3. Jeffrey Ullman
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  4. Jennifer Widom
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  5. Yehoshua Sagiv
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Quass, D., Rajaraman, A., Ullman, J. et al. Querying Semistructured Heterogeneous Information. Journal of Systems Integration 7, 381–407 (1997). https://doi.org/10.1023/A:1008287522472

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