Data Quality in Web Information Systems

  • Barbara Pernici
  • Monica Scannapieco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2800)


Evaluation of data quality in web information systems provides support for a correct interpretation of the contents of web pages. Data quality dimensions proposed in the literature need to be adapted and extended to represent the characteristics of data in web pages, and in particular their dynamic aspects. The present paper proposes and discusses a model and a methodological framework to support data quality in web information systems. The design and a prototype implementation of a software module to publish quality information are also described.


Data Quality Quality Dimension Resource Description Framework Source Reliability Methodological Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Atzeni, P., Merialdo, P., Sindoni, G.: Web Site Evaluation: Methodology and Case Study. In: Proceedings of DASWIS 2001: International Workshop on Data Semantics in Web Information Systems, Yokohama, Japan (2001)Google Scholar
  2. 2.
    Ballou, D.P., Pazer, H.L.: Modeling data and process quality in multi-input, multi-output information systems. Management Science 31(2) (1985)Google Scholar
  3. 3.
    Barnes, S.J., Vidgen, R.T.: Assessing the Quality of Auction Web Sites. In: Proceedings of the 34th Annual Hawaii International Conference on System Sciences (HICSS-34), Maui, Hawaii (2001)Google Scholar
  4. 4.
    Batini, C., Lenzerini, M., Navathe, S.B.: A Comparative Analysis of Methodologies for Database Schema Integration. ACM Computing Survey 15(4) (1984)Google Scholar
  5. 5.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American (May 2001)Google Scholar
  6. 6.
    Bertolazzi, P., Scannapieco, M.: Introducing Data Quality in a Cooperative Context. In: Proceedings of the 6th International Conference on Information Quality (IQ 2001), Boston, MA, USA (2001)Google Scholar
  7. 7.
    Brickley, D., Guha, R.V. (eds.): RDF Vocabulary Description Language 1.0: RDF Schema. W3C Working Draft, 23 (January 2003) Google Scholar
  8. 8.
    Dasu, T., Johnson, T., Muthukrishnan, S., Shkapenyuk, V.: Mining Database Structure or How to Build a Data Quality Browser. In: Proceedings of the 2002 ACM/SIGMOD Conference, Madison, WI, USA (2002)Google Scholar
  9. 9.
    Galhardas, H., Florescu, D., Shasha, D., Simon, E.: An Extensible Framework for Data Cleaning. In: Proceedings of the 16th International Conference on Data Engineering (ICDE 2000), San Diego, California, CA (2000)Google Scholar
  10. 10.
    Garzotto, F., Mainetti, L., Paolini, P.: Hypermedia Design, Analysis and Evaluation Issues. Communication of the ACM 58(8) (1995)Google Scholar
  11. 11.
    Katerattanakul, P., Siau, K.: Measuring Information Quality of Web Sites: Development of an Instrument. In: Proceedings of the International Conference on Information Systems (ICIS 1999), Charlotte, North Carolina, USA (1999)Google Scholar
  12. 12.
    Isakowitz, T., Bieber, M., Vitali, F. (eds.): Web Information Systems (Special Issue). Communications of the ACM 41(7) (1998)Google Scholar
  13. 13.
    Isakowitz, T., Kamis, A., Koufaris, M.: The Extended RMM Methodology for Web Publishing. Working Paper IS-98-18, Center for Research on Information Systems, University of Pennsylvania, Philadelphia, PA, USA (1998)Google Scholar
  14. 14.
    Isakowitz, T., Stohr, E.A., Balasubramanian, P.: RMM: a Methodology for Structured Hypermedia Design. Communications of the ACM 58(8) (1995)Google Scholar
  15. 15.
    Lassila, O., Swick, R.R. (eds.): Resource Description Framework (RDF) Model and Syntax Specification. W3C Recommendation, February 22 (1999)Google Scholar
  16. 16.
    Mecca, G., Merialdo, P., Atzeni, A., Crescenzi, V.: The (short) ARANEUS Guide to Web-Site Development. In: Proceedings of the Second International Workshop on the Web and Databases (WebDB 1999) in conjunction with SIGMOD 1999, Philadelphia, Pennsylvania, USA (1999)Google Scholar
  17. 17.
    Mihaila, G., Raschid, L., Vidal, M.: Querying Quality of Data Metadata. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, p. 87. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  18. 18.
    Naumann, F.: Quality-Driven Query Answering for Integrated Information Systems. LNCS, vol. 2261. Springer, Heidelberg (2002)MATHCrossRefGoogle Scholar
  19. 19.
    Murugesan, S., Desphande, Y. (eds.): Web Engineering. LNCS, vol. 2016. Springer, Heidelberg (2001)MATHGoogle Scholar
  20. 20.
    Pipino, L., Lee, Y., Wang, R.: Data Quality Assessment. Communications of the ACM 45(4) (2002)Google Scholar
  21. 21.
    Redman, T.C.: Data Quality for the Information Age. Artech House (1996)Google Scholar
  22. 22.
    Tansell, A., Snodgrass, R., Clifford, J., Gadia, S., Segev, A. (eds.): Temporal Databases. Benjamin-Cummings, Redwood city (1993)Google Scholar
  23. 23.
    Wand, Y., Wang, R.Y.: Anchoring Data Quality Dimensions in Ontological Foundations. Communications of the ACM 39(11) (1996)Google Scholar
  24. 24.
    Wang, R.Y.: A Product Perspective on Total Data Quality Management. Communication of the ACM 41(2) (1998)Google Scholar
  25. 25.
    Wang, R.Y., Storey, V.C., Firth, C.P.: A Framework for Analysis of Data Quality Research. IEEE Transaction on Knowledge and Data Engineering 7(4) (1995)Google Scholar
  26. 26.
    Wang, R.Y., Strong, D.M.: Beyond Accuracy: What Data Quality Means to Data Consumers. Journal of Management Information Systems 12(4) (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Barbara Pernici
    • 1
  • Monica Scannapieco
    • 2
  1. 1.Dipartimento di Elettronica e InformazionePolitecnico di MilanoMilanoItaly
  2. 2.Dipartimento di Informatica e SistemisticaUniversità di Roma “La Sapienza”RomaItaly

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