Abstract
Concerns over data-processing activities that may lead to privacy violations or harms have motivated the development of legal frameworks and standards to govern the processing of personal data. However, it is widely recognised that there is a disconnect between policy-makers’ intentions and software engineering reality. The Abstract Personal Data Lifecycle (APDL) model, which was proposed to serve as an abstract model for personal data life-cycles, distinguishes between the main operations that can be performed on personal data during its lifecycle by outlining the various distinct activities for each operation. We show how the APDL can be represented in terms of the Unified Modeling Language (UML). The profile is illustrated via a realistic case study.
Cite
CITATION STYLE
Alshammari, M., & Simpson, A. (2018). A UML profile for privacy-aware data lifecycle models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10683 LNCS, pp. 189–209). Springer Verlag. https://doi.org/10.1007/978-3-319-72817-9_13
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