语义网中的知识组织系统（KOS）：一个多维度的综述
Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review
摘要：
自从简单知识组织系统（SKOS）规范及其标签扩展（SKOS-XL）在2009年成为正式的W3C建议以来，大量的传统知识组织系统（KOS）（包括叙词表，分类方案，名称权威机构，以及在本体浪潮到来之前产生的代码和术语列表）已经加入了语义网的主流。本文使用“LOD KOS”作为一个总括术语来指代语义Web框架内的所有值词汇表和轻量级本体。本文概述了LOD KOS运动给各个社区和用户带来的影响。这些并不局限于价值词汇表构造者和提供者的群体，也不局限于有着将词汇表应用于其产品的悠久历史的编目员和索引员。LOD数据集制作者和LOD服务提供商、信息架构师和界面设计师以及科学和人文领域的研究人员也是LOD KOS的直接受益者。本文研究了一组收集的案例（实验或在实际应用中），旨在找到LOD KOS的用法，以便在社区和用户之间分享实践和想法。通过多个不同用户组的观点，从多个维度考察了LOD KOS的功能。本文重点介绍了LOD数据集生产者，词汇生产者和研究人员（作为KOS的最终用户）。
英文摘要：
Since the Simple Knowledge Organization System (SKOS) specification and its SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a significant number of conventional knowledge organization systems (KOS) (including thesauri, classification schemes, name authorities, and lists of codes and terms, produced before the arrival of the ontology-wave) have made their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS" as an umbrella term to refer to all of the value vocabularies and lightweight ontologies within the Semantic Web framework. The paper provides an overview of what the LOD KOS movement has brought to various communities and users. These are not limited to the colonies of the value vocabulary constructors and providers, nor the catalogers and indexers who have a long history of applying the vocabularies to their products. The LOD dataset producers and LOD service providers, the information architects and interface designers, and researchers in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper examines a set of the collected cases (experimental or in real applications) and aims to find the usages of LOD KOS in order to share the practices and ideas among communities and users. Through the viewpoints of a number of different user groups, the functions of LOD KOS are examined from multiple dimensions. This paper focuses on the LOD dataset producers, vocabulary producers, and researchers (as end-users of KOS).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
