Logic can define how agents are provided or denied access to resources, how to interlink resources using mining processes and provide users with choices for possible next steps in a workflow. These decisions are for the most part hidden, internal to machines processing data. In order to exchange this internal logic a portable Web logic is required which the Semantic Web could provide. Combining logic and data provides insights into the reasoning process and creates a new level of trust on the Semantic Web. Current Web logics carries only a fragment of first-order logic (FOL) to keep exchange languages decidable or easily processable. But, this is at a cost: the portability of logic. Machines require implicit agreements to know which fragment of logic is being exchanged and need a strategy for how to cope with the different fragments. These choices could obscure insights into the reasoning process. We created RDF Surfaces in order to express the full expressivity of FOL including saying explicitly `no'. This vision paper provides basic principles and compares existing work. Even though support for FOL is semi-decidable, we argue these problems are surmountable. RDF Surfaces span many use cases, including describing misuse of information, adding explainability and trust to reasoning, and providing scope for reasoning over streams of data and queries. RDF Surfaces provide the direct translation of FOL for the Semantic Web. We hope this vision paper attracts new implementers and opens the discussion to its formal specification.

翻译：逻辑可以定义代理如何被授予或拒绝资源访问权限，如何利用挖掘过程实现资源互联，并为用户提供工作流中下一步操作的选择。这些决策大部分是隐藏的，仅在处理数据的机器内部运作。为了交换这种内部逻辑，需要一种可移植的网络逻辑，而语义网可以提供这一点。将逻辑与数据相结合，能够揭示推理过程的内部机制，并在语义网上建立新的信任层级。当前网络逻辑仅承载一阶逻辑的片段，以保持交换语言的可判定性或易处理性。但这带来了代价：逻辑的可移植性受损。机器需要隐式协议来识别所交换的逻辑片段，并制定策略以应对不同片段之间的差异。这些选择可能模糊对推理过程的洞察。我们创建了RDF曲面，以表达一阶逻辑的全部表达能力，包括明确说出"不"。这篇愿景论文阐述了基本原则，并与现有工作进行了比较。尽管对一阶逻辑的支持是半可判定的，但我们认为这些问题是可以克服的。RDF曲面涵盖诸多用例，包括描述信息滥用、为推理增加可解释性和可信度，以及为数据流和查询的推理提供范围。RDF曲面为一阶逻辑在语义网中的直接翻译提供了方案。我们希望这篇愿景论文能吸引更多实现者，并开启对其形式化规范的讨论。