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ShareAlike Your Data: Self-referential Usage Policies for the Semantic Web

机译:与您的数据相同的共享:语义网的自引用使用策略

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Numerous forms of policies, licensing terms, and related conditions are associated with Web data and services. A natural goal for facilitating the reuse and re-combination of such content is to model usage policies as part of the data so as to enable their exchange and automated processing. This paper thus proposes a concrete policy modelling language. A particular difficulty are self-referential policies such as Creative Commons ShareAlike, that mandate that derived content is published under some license with the same permissions and requirements. We present a general semantic framework for evaluating such recursive statements, show that it has desirable formal properties, and explain how it can be evaluated using existing tools. We then show that our approach is compatible with both OWL DL and Datalog, and illustrate how one can concretely model self-referential policies in these languages to obtain desired conclusions.
机译:多种形式的策略,许可条款和相关条件与Web数据和服务相关联。促进此类内容的重用和重新组合的自然目标是将使用策略建模为数据的一部分,以使它们能够进行交换和自动处理。因此,本文提出了一种具体的策略建模语言。一个特别的困难是诸如Creative Commons ShareAlike之类的自引用策略,该策略要求派生的内容必须在具有相同许可权和要求的某些许可下发布。我们提供了一种用于评估此类递归语句的通用语义框架,表明它具有理想的形式属性,并说明了如何使用现有工具对其进行评估。然后,我们证明了我们的方法与OWL DL和Datalog都兼容,并说明了如何在这些语言中具体建模自引用策略以获得所需的结论。

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