The Anonymisation Decision-making Framework (ADF) operationalizes the risk management of data exchange between organizations, referred to as "data environments". The second edition of ADF has increased its emphasis on modeling data flows, highlighting a potential new use of provenance information to support anonymisation decision-making. In this paper, we provide a use case that showcases this functionality more. Based on this use case, we identify how provenance information could be utilized within the ADF framework, and identify a currently un-met requirement which is the modeling of \textit{data environments}. We show how data environments can be implemented within the W3C PROV in four different ways. We analyze the costs and benefits of each approach, and consider another use case as a partial check for completeness. We then summarize our findings and suggest ways forward.
@article{arxiv.2107.09966,
title = {Provenance, Anonymisation and Data Environments: a Unifying Construction},
author = {Muhammad Aslam Jarwar and Adriane Chapman and Mark Elliot and Fatemeh Raji},
journal= {arXiv preprint arXiv:2107.09966},
year = {2021}
}