Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Data Quality Models

  • Monica ScannapiecoEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_109


Data quality representations


Data quality models extend traditional models for databases for the purpose of representing data quality dimensions and the association of such dimensions to data. Therefore, data quality models allow: (i) the analysis of a set of data quality requirements and their representation in terms of conceptual schemas; (ii) accessing and querying data quality dimensions by means of logical schemas. Data quality models also include process models tailored to the analysis and design of quality improvement actions. These models permit tracking data from their source, through various manipulations that data can undergo, to their final usage. In this way, they support the detection of causes of poor data quality and the design of improvement actions.

Historical Background

Among the first data quality models, in 1990 the polygen model [6] was proposed for explicitly tracing the origins of data and the intermediate sources used to arrive at that...

This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 1.
    Batini C, Scannapieco M. Data quality: concepts, methodologies, and techniques. Berlin: Springer; 2006.zbMATHGoogle Scholar
  2. 2.
    Scannapieco M, Pernici B, Pierce EM. IP-UML: towards a methodology for quality improvement based on the IP-MAP framework. In: Proceedings of the 7th International Conference on Information Quality; 2002.Google Scholar
  3. 3.
    Scannapieco M, Virgillito A, Marchetti C, Mecella M, Baldoni R. The DaQuinCIS architecture: a platform for exchanging and improving data quality in cooperative information systems. Inf Syst. 2004;29(7):551–82.CrossRefGoogle Scholar
  4. 4.
    Shankaranarayan G, Wang RY, Ziad M. Modeling the manufacture of an information product with IP-MAP. In: Proceedings of the 5th International Conference on Information Quality; 2000. p. 1–16.Google Scholar
  5. 5.
    Storey VC, Wang RY. An analysis of quality requirements in database design. In: Proceedings of the 4th International Conference on Information Quality; 1998. p. 64–87.Google Scholar
  6. 6.
    Wang RY, Madnick SE. A polygen model for heterogeneous database systems: the source tagging perspective. In: Proceedings of the 16th International Conference on Very Large Data Bases; 1990. p. 519–38.Google Scholar
  7. 7.
    Wang RY, Reddy MP, Kon H. Toward data quality: an attribute-based approach. Decis Support Syst. 1995;13(3–4):349–72.CrossRefGoogle Scholar
  8. 8.
    Wang RY, Ziad M, Lee YW. Data quality. Boston: Kluwer; 2001.zbMATHGoogle Scholar
  9. 9.
    W3C Working Group. An overview of the PROV family of documents. Available at: http://www.w3.org/TR/prov-overview/

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of RomeRomeItaly

Section editors and affiliations

  • Felix Naumann
    • 1
  1. 1.Information SystemsHasso-Plattner-InstitutePotsdamGermany