  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.
