Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Database Systems pp 1955–1958Cite as

Information Quality Assessment

  • Reference work entry
  • First Online:

  • 17 Accesses

Synonyms

Data; Information

Definition

This entry uses the terms data and information interchangeably. The classical distinction is that data are raw facts whereas information is data in context or data that have been processed. Nevertheless, other than at an abstract level, it is a distinction that is often not made and one finds that the terms are used interchangeably. It is important to note that one individual’s information can be data to another individual. This entry will also use the terms information quality dimension and information quality variable interchangeably.

Further, this chapter defines information of quality as information that is fit for use (or data of quality as data that is fit for use). This means that context and use plays an important role in evaluating information quality. For example, the instantaneous changes in a stock’s price may be of importance to the stock trader who may trade stocks on a minute by minute basis. This instantaneous information, however,...

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   6,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Recommended Reading

  1. Ballou D, Pazer H. Modeling data and process quality in multi-input, multi-output information systems. Manag Sci. 1985;31(2):150–62.

    Article  Google Scholar 

  2. Ballou D, Wang R, Pazer H, Tayi G. Modeling information manufacturing systems to determine information product quality. Manag Sci. 1998;44(4):462–84.

    Article  MATH  Google Scholar 

  3. Batini C, Scannapieco M. Data quality: concepts, methodologies and techniques. New York: Springer; 2006.

    MATH  Google Scholar 

  4. Codd E. The relational model for database management: version 2. Reading: Addison-Wesley; 1990.

    MATH  Google Scholar 

  5. Eden A, Shankaranarayanan G. Understanding impartial versus utility-driven quality assessment in large datasets. In: Proceedings of the 12th Conference on Information Quality; 2007. p. 265–79.

    Google Scholar 

  6. Huang K, Lee. Y, Wang R. Quality information and knowledge. Englewood Cliffs: Prentice-Hall; 1999.

    Google Scholar 

  7. Krantz D, Luce R, Suppes P, Tversky A. Foundations of measurement: additive and polynomial representation. New York: Academic; 1971.

    MATH  Google Scholar 

  8. Lee YW, Pipino LL, Funk JD, Wang RY. Journey to data quality. Cambridge: MIT Press; 2006.

    Google Scholar 

  9. Pipino L, Lee Y, Wang R. Data quality assessment. Commun ACM. 2002;45(4):211–8.

    Article  Google Scholar 

  10. Redman T. Data quality: the field guide. Belford: Digital Press; 2001.

    Google Scholar 

  11. Strong D, Lee Y, Wang R. Data quality in context. Commun ACM. 1997;40(5):103–10.

    Article  Google Scholar 

  12. Wang R, Lee Y, Pipino L, Strong D. Manage your information as a product. Sloan Manag Rev. 1998;39(4):95–105.

    Google Scholar 

  13. Wang R, Strong D. Beyond accuracy: what data quality means to data consumers. J Manag Inf Syst. 1996;12(4):5–34.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Massachusetts, Lowell, MA, USA

    Leo L. Pipino

Authors
  1. Leo L. Pipino
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Leo L. Pipino .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. College of Business Administration, Northeastern Univ., Boston, MA, USA

    Yang W. Lee

Rights and permissions

Reprints and permissions

Copyright information

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

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Pipino, L.L. (2018). Information Quality Assessment. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_496

Download citation

Publish with us

Policies and ethics

Search

Navigation