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.

中文翻译：

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来源、匿名化和数据环境：一个统一的结构

匿名化决策框架 (ADF) 实施组织之间数据交换的风险管理，称为“数据环境”。ADF 的第二版更加强调数据流建模，突出了来源信息的潜在新用途，以支持匿名化决策。在本文中，我们提供了一个更多展示此功能的用例。基于此用例，我们确定了如何在 ADF 框架内利用出处信息，并确定当前未满足的需求，即 \textit{数据环境} 的建模。我们展示了如何以四种不同的方式在 W3C PROV 中实现数据环境。我们分析每种方法的成本和收益，并考虑另一个用例作为完整性的部分检查。