摘要翻译：
对学术工件使用的大规模分析主要受到使用数据归档的当前实践、与使用数据传播有关的隐私问题以及缺乏用于建模使用领域的实用本体的限制。作为对第三个限制的补救，本文提出了一个学术本体，它被设计来表示那些存在大规模书目和使用数据的类，支持使用研究，其实例化可伸缩到5000万篇文章及其相关的工件（例如作者和期刊）和伴随的10亿个使用事件。所提出的抽象本体的现实世界实例化是学术社区的语义网络模型，它将学术过程提供给统计分析和计算支持。我们提出了本体，讨论了它的实例化，并提供了一些用于计算各种学术工件度量的示例推理规则。
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英文标题：
《A Practical Ontology for the Large-Scale Modeling of Scholarly Artifacts
  and their Usage》
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作者：
Marko A. Rodriguez, Johah Bollen, Herbert Van de Sompel
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最新提交年份：
2007
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分类信息：

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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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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英文摘要：
  The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real world instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. We present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.
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PDF链接：
https://arxiv.org/pdf/0708.1150