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A systematic methodology for privacy impact assessments: a design science approach

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  • Marie Caroline Oetzel
  • Sarah Spiekermann

Abstract

For companies that develop and operate IT applications that process the personal data of customers and employees, a major problem is protecting these data and preventing privacy breaches. Failure to adequately address this problem can result in considerable damage to the company's reputation and finances, as well as negative effects for customers or employees (data subjects). To address this problem, we propose a methodology that systematically considers privacy issues by using a step-by-step privacy impact assessment (PIA). Existing PIA approaches cannot be applied easily because they are improperly structured or imprecise and lengthy. We argue that companies that employ our PIA can achieve ‘privacy-by-design’, which is widely heralded by data protection authorities. In fact, the German Federal Office for Information Security (BSI) ratified the approach we present in this article for the technical field of RFID and published it as a guideline in November 2011. The contribution of the artefacts we created is twofold: First, we provide a formal problem representation structure for the analysis of privacy requirements. Second, we reduce the complexity of the privacy regulation landscape for practitioners who need to make privacy management decisions for their IT applications.

Suggested Citation

  • Marie Caroline Oetzel & Sarah Spiekermann, 2014. "A systematic methodology for privacy impact assessments: a design science approach," European Journal of Information Systems, Taylor & Francis Journals, vol. 23(2), pages 126-150, March.
  • Handle: RePEc:taf:tjisxx:v:23:y:2014:i:2:p:126-150
    DOI: 10.1057/ejis.2013.18
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    Cited by:

    1. Palladino, Nicola, 2023. "A ‘biased’ emerging governance regime for artificial intelligence? How AI ethics get skewed moving from principles to practices," Telecommunications Policy, Elsevier, vol. 47(5).

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