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Using Schematically Heterogeneous Structures.

Renée J. Miller: Using Schematically Heterogeneous Structures. SIGMOD Conference 1998: 189-200
@inproceedings{DBLP:conf/sigmod/Miller98,
  author    = {Ren{\'e}e J. Miller},
  editor    = {Laura M. Haas and
               Ashutosh Tiwary},
  title     = {Using Schematically Heterogeneous Structures},
  booktitle = {SIGMOD 1998, Proceedings ACM SIGMOD International Conference
               on Management of Data, June 2-4, 1998, Seattle, Washington, USA},
  publisher = {ACM Press},
  year      = {1998},
  isbn      = {0-89791-995-5},
  pages     = {189-200},
  ee        = {http://doi.acm.org/10.1145/276304.276322, db/conf/sigmod/Miller98.html},
  crossref  = {DBLP:conf/sigmod/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Schematic heterogeneity arises when information that is represented as data under one schema, is represented within the schema (as metadata) in another. Schematic heterogeneity is an important class of heterogeneity that arises frequently in integrating legacy data in federated or data warehousing applications. Traditional query languages and view mechanisms are insufficient for reconciling and translating data between schematically heterogeneous schemas. Higher order query languages, that permit quantification over schema labels, have been proposed to permit querying and restructuring of data between schematically disparate schemas. We extend this work by considering how these languages can be used in practice. Specifically, we consider a restricted class of higher order views and show the power of these views in integrating legacy structures. Our results provide insights into the properties of restructuring transformations required to resolve schematic discrepancies. In addition, we show how the use of these views permits schema browsing and new forms of data independence that are important for global information systems. Furthermore, these views provide a framework for integrating semi-structured and unstructured queries, such as keyword searches, into a structured querying environment. We show how these views can be used with minimal extensions to existing query engines. We give conditions under which a higher order view is usable for answering a query and provide query translation algorithms.

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Laura M. Haas, Ashutosh Tiwary (Eds.): SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, USA. ACM Press 1998, ISBN 0-89791-995-5 BibTeX , SIGMOD Record 27(2), June 1998
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Referenced by

  1. Renée J. Miller, Laura M. Haas, Mauricio A. Hernández: Schema Mapping as Query Discovery. VLDB 2000: 77-88
  2. Laura M. Haas, Renée J. Miller, B. Niswonger, Mary Tork Roth, Peter M. Schwarz, Edward L. Wimmers: Transforming Heterogeneous Data with Database Middleware: Beyond Integration. IEEE Data Eng. Bull. 22(1): 31-36(1999)
  3. Laks V. S. Lakshmanan, Fereidoon Sadri, Subbu N. Subramanian: On Efficiently Implementing SchemaSQL on an SQL Database System. VLDB 1999: 471-482
BibTeX
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