ProvAbs：用于抽象PROV图的模型、策略和工具
ProvAbs: model, policy, and tooling for abstracting PROV graphs
摘要：
来源元数据在数据共享环境中可能很有价值，可用于帮助数据消费者对第三方产生的数据的可靠性作出判断。然而，出处的某些部分可能是敏感的，需要访问控制，或者它们可能需要针对目标受众进行简化。这两个问题都可以通过一个单独的机制来解决，该机制用于在起源上创建抽象，并与驱动抽象的策略模型相结合。这种机制，我们称之为分组抽象，同时实现了部分披露的出处，并促进其消费。在本文中，我们介绍了一个正式的基础，这种类型的抽象，接地W3C PROV模型，描述了相关的政策模型，并简要介绍了其实现，Provabs工具的政策和抽象的互动实验。
英文摘要：
Provenance metadata can be valuable in data sharing settings, where it can be used to help data consumers form judgements regarding the reliability of the data produced by third parties. However, some parts of provenance may be sensitive, requiring access control, or they may need to be simplified for the intended audience. Both these issues can be addressed by a single mechanism for creating abstractions over provenance, coupled with a policy model to drive the abstraction. Such mechanism, which we refer to as abstraction by grouping, simultaneously achieves partial disclosure of provenance, and facilitates its consumption. In this paper we introduce a formal foundation for this type of abstraction, grounded in the W3C PROV model; describe the associated policy model; and briefly present its implementation, the Provabs tool for interactive experimentation with policies and abstractions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
