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Protecting Anonymity in Data-Driven Biomedical Science

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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8401))

Abstract

With formidable recent improvements in data processing and information retrieval, knowledge discovery/data mining, business intelligence, content analytics and other upcoming empirical approaches have an enormous potential, particularly for the data intensive biomedical sciences. For results derived using empirical methods, the underlying data set should be made available, at least during the review process for the reviewers, to ensure the quality of the research done and to prevent fraud or errors and to enable the replication of studies. However, in particular in the medicine and the life sciences, this leads to a discrepancy, as the disclosure of research data raises considerable privacy concerns, as researchers have of course the full responsibility to protect their (volunteer) subjects, hence must adhere to respective ethical policies. One solution for this problem lies in the protection of sensitive information in medical data sets by applying appropriate anonymization. This paper provides an overview on the most important and well-researched approaches and discusses open research problems in this area, with the goal to act as a starting point for further investigation.

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Author information

Authors and Affiliations

  1. Secure Business Austria Research, Austria

    Peter Kieseberg, Heidelinde Hobel & Edgar Weippl

  2. Research Unit HCI, Institute for Medical Informatics, Statistics & Documentation, Medical University Graz, Austria

    Peter Kieseberg & Andreas Holzinger

  3. University of Applied Sciences, St. Pölten, Austria

    Sebastian Schrittwieser

Authors
  1. Peter Kieseberg
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  2. Heidelinde Hobel
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  3. Sebastian Schrittwieser
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  4. Edgar Weippl
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  5. Andreas Holzinger
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Editor information

Editors and Affiliations

  1. Research Unit Human-Computer Interaction, Austrian IBM Watson Think Gruop, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2/V, 8036, Graz, Austria

    Andreas Holzinger

  2. IBM Life Sciences Discovery Centre, TECHNA for the Advancement of Technology for Health, Princess Margaret Cancer Centre, University Health Network, TMDT Room 11-314, 101 College Street, M5G 1L7, Toronto, ON, Canada

    Igor Jurisica

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Kieseberg, P., Hobel, H., Schrittwieser, S., Weippl, E., Holzinger, A. (2014). Protecting Anonymity in Data-Driven Biomedical Science. In: Holzinger, A., Jurisica, I. (eds) Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. Lecture Notes in Computer Science, vol 8401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43968-5_17

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  • DOI: https://doi.org/10.1007/978-3-662-43968-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43967-8

  • Online ISBN: 978-3-662-43968-5

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