Expressing and processing timeliness quality aware queries: the DQ2L approach

  • Authors:
  • Chao Dong;Sandra de F. Mendes Sampaio;Pedro R. Falcone Sampaio

  • Affiliations:
  • School of Informatics, University of Manchester, Manchester;School of Informatics, University of Manchester, Manchester;School of Informatics, University of Manchester, Manchester

  • Venue:
  • CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
  • Year:
  • 2006

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Abstract

With the growing need for querying and combining data from multiple data sources, data analysts, database application programmers and advanced database users are increasingly facing the problem of filtering out low quality data with regard to the intended use. This paper investigates the problem of expressing and processing data quality requests during quality-aware query formulation. The paper proposes the Data Quality Query Language (DQ2L), an extension of SQL aimed at enabling query language users to express data quality requests and a query processing framework (architecture, query processing stages, metadata support and quality model) aimed at extending relational query processing with quality-aware query processing structures and techniques. The paper focuses on the timeliness data quality dimension.