摘要翻译：
新兴的数据网络利用Web基础设施来表示和关联数据。数据Web的基本标准包括统一资源标识符(URI)和资源描述框架(RDF)。URI用于标识资源，RDF用于关联资源。虽然RDF被认为是一种专门为知识表示和推理而设计的逻辑语言，但如果它能方便地支持其他计算模型，它就会更加有用。为了实现数据Web作为存储和处理世界数据的通用媒体，有必要将RDF从其逻辑语言遗产中分离出来，并将其简单地框架化为数据模型。此外，将语义Web看作是对数据Web的一种特殊解释，它特别关注于知识表示和推理，这是一个显著的优势。通过这样做，暴露了数据网络的其他解释，这些解释以不同的能力实现RDF，并支持不同的计算模型。
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英文标题：
《Interpretations of the Web of Data》
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作者：
Marko A. Rodriguez
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最新提交年份：
2009
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Digital Libraries        数字图书馆
分类描述：Covers all aspects of the digital library design and document and text creation. Note that there will be some overlap with Information Retrieval (which is a separate subject area). Roughly includes material in ACM Subject Classes H.3.5, H.3.6, H.3.7, I.7.
涵盖了数字图书馆设计和文献及文本创作的各个方面。注意，与信息检索（这是一个单独的主题领域）会有一些重叠。大致包括ACM课程H.3.5、H.3.6、H.3.7、I.7中的材料。
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英文摘要：
  The emerging Web of Data utilizes the web infrastructure to represent and interrelate data. The foundational standards of the Web of Data include the Uniform Resource Identifier (URI) and the Resource Description Framework (RDF). URIs are used to identify resources and RDF is used to relate resources. While RDF has been posited as a logic language designed specifically for knowledge representation and reasoning, it is more generally useful if it can conveniently support other models of computing. In order to realize the Web of Data as a general-purpose medium for storing and processing the world's data, it is necessary to separate RDF from its logic language legacy and frame it simply as a data model. Moreover, there is significant advantage in seeing the Semantic Web as a particular interpretation of the Web of Data that is focused specifically on knowledge representation and reasoning. By doing so, other interpretations of the Web of Data are exposed that realize RDF in different capacities and in support of different computing models.
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PDF链接：
https://arxiv.org/pdf/0905.3378