摘要翻译：
资源描述框架（Resource Description Framework,RDF）正在继续发展，超出其最初作为元数据框架的功能范围，进入通用数据建模领域。RDF数据库存储库的容量和速度不断提高，称为三元存储，促进了这种扩展。高端RDF三元存储可以容纳和处理100亿个三元存储。为了提供RDF存储库中包含的数据的无缝集成，链接数据社区提供了将RDF数据集链接到一个通用分布式图中的规范，该图可以由人和机器遍历。虽然RDF数据集的无缝集成很重要，但以目前存在并将最终发展成为的数据集的规模来看，万维网的“下载和索引”哲学将不那么容易映射到语义网。本文讨论了在当前分布式RDF数据结构中添加分布式RDF过程基础结构的重要性。
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英文标题：
《A Distributed Process Infrastructure for a Distributed Data Structure》
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作者：
Marko A. Rodriguez
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最新提交年份：
2008
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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 Resource Description Framework (RDF) is continuing to grow outside the bounds of its initial function as a metadata framework and into the domain of general-purpose data modeling. This expansion has been facilitated by the continued increase in the capacity and speed of RDF database repositories known as triple-stores. High-end RDF triple-stores can hold and process on the order of 10 billion triples. In an effort to provide a seamless integration of the data contained in RDF repositories, the Linked Data community is providing specifications for linking RDF data sets into a universal distributed graph that can be traversed by both man and machine. While the seamless integration of RDF data sets is important, at the scale of the data sets that currently exist and will ultimately grow to become, the "download and index" philosophy of the World Wide Web will not so easily map over to the Semantic Web. This essay discusses the importance of adding a distributed RDF process infrastructure to the current distributed RDF data structure.
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PDF链接：
https://arxiv.org/pdf/0807.3908