IDEAS home Printed from https://ideas.repec.org/p/mit/sloanp/40086.html
   My bibliography  Save this paper

Measuring Data Believability: A Provenance Approach

Author

Listed:
  • Prat, Nicolas
  • Madnick, Stuart E.

Abstract

Data quality is crucial for operational efficiency and sound decision making. This paper focuses on believability, a major aspect of quality, measured along three dimensions: trustworthiness, reasonableness, and temporality. We ground our approach on provenance, i.e. the origin and subsequent processing history of data. We present our provenance model and our approach for computing believability based on provenance metadata. The approach is structured into three increasingly complex building blocks: (1) definition of metrics for assessing the believability of data sources, (2) definition of metrics for assessing the believability of data resulting from one process run and (3) assessment of believability based on all the sources and processing history of data. We illustrate our approach with a scenario based on Internet data. To our knowledge, this is the first work to develop a precise approach to measuring data believability and making explicit use of provenance-based measurements.

Suggested Citation

  • Prat, Nicolas & Madnick, Stuart E., 2008. "Measuring Data Believability: A Provenance Approach," Working papers 40086, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    • Handle: RePEc:mit:sloanp:40086
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/1721.1/40086
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Steven Tadelis, 2003. "Firm reputation with hidden information," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 21(2), pages 635-651, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Prat, Nicolas & Madnick, Stuart E., 2008. "Evaluating and Aggregating Data Believability across Quality Sub-Dimensions and Data Lineage," Working papers 40085, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Nicolas Prat, 2019. "Augmented Analytics," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 375-380, June.
    3. Vliegen, Lea & Moroff, Nikolas Ulrich & Riehl, Katharina, 2020. "Evaluation of data quality in dimensioning capacity," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 355-394, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olivier Gergaud & Florine Livat, 2004. "Team versus individual reputations: a model of interaction and some empirical evidence," Cahiers de la Maison des Sciences Economiques bla04015, Université Panthéon-Sorbonne (Paris 1).
    2. Guillermo Ordoñez, 2013. "Reputation from nested activities," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(3), pages 915-940, April.
    3. Heski Bar-Isaac, 2004. "Something to Prove: Reputation in teams and hiring to introduce uncertainty," Working Papers 04-07, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Omer Moav & Zvika Neeman, 2010. "The Quality Of Information And Incentives For Effort," Journal of Industrial Economics, Wiley Blackwell, vol. 58(3), pages 642-660, September.
    5. Steven Tadelis, 1999. "What's in a Name? Reputation as a Tradeable Asset," American Economic Review, American Economic Association, vol. 89(3), pages 548-563, June.
    6. Howard P. Marvel & Lixin Ye, 2008. "Trademark Sales, Entry, And The Value Of Reputation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(2), pages 547-576, May.
    7. Wiseman, Thomas, 2008. "Reputation and impermanent types," Games and Economic Behavior, Elsevier, vol. 62(1), pages 190-210, January.
    8. Bendell, Bari L. & Kristal, Emma K., 2023. "Five naming strategies to help tell your organization’s story," Business Horizons, Elsevier, vol. 66(3), pages 387-404.
    9. Joyee Deb, 2012. "Observability and Sorting in a Market for Names," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 21(2), pages 301-338, June.
    10. Wang, Tianxi, 2007. "The Reputation of an Organization and its Dynamics," Economics Discussion Papers 2954, University of Essex, Department of Economics.
    11. Hakenes, Hendrik & Peitz, Martin, 2004. "Selling Reputation When Going out of Business," Sonderforschungsbereich 504 Publications 04-52, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    12. Chen, Yong & Mak, Barry & Li, Zhou, 2013. "Quality deterioration in package tours: The interplay of asymmetric information and reputation," Tourism Management, Elsevier, vol. 38(C), pages 43-54.
    13. Christopher Chambers & Paul Healy, 2012. "Updating toward the signal," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 50(3), pages 765-786, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mit:sloanp:40086. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: None (email available below). General contact details of provider: https://edirc.repec.org/data/ssmitus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.