Reasoning about the appropriate use of private data through computational workflows

Abstract

While there is a plethora of mechanisms to ensure lawful access to privacy-protected data, additional research is required in order to reassure individuals that their personal data is being used for the purpose that they consented to. This is particularly important in the context of new data mining approaches, as used, for instance, in biomedical research and commercial data mining. We argue for the use of computational workflows to ensure and enforce appropriate use of sensitive personal data. Computational workflows describe in a declarative manner the data processing steps and the expected results of complex data analysis processes such as data mining (Gil et al. 2007b; Taylor et al. 2006). We see workflows as an artifact that captures, among other things, how data is being used and for what purpose. Existing frameworks for computational workflows need to be extended to incorporate privacy policies that can govern the use of data.