Please wait a minute...
New Technology of Library and Information Service  2011, Vol. 27 Issue (6): 79-84    DOI: 10.11925/infotech.1003-3513.2011.06.13
Current Issue | Archive | Adv Search |
Review on Converting Enumerative Classification Schemes to SKOS
He Lin1, Du Huiping2
1. Department of Information Management, Nanjing Agriculture University,Nanjing 210095, China;
2. Library of Shanghai Normal University, Shanghai 200234, China
Export: BibTeX | EndNote (RIS)      
Abstract  The paper introduces the development of converting classification schemes to SKOS, especially with emphasis on the difficulties during the converting process. It also proposes some probably resolved solutions now and in the future,and prospects the research fields. The authors expect it can be useful for the exchange of machine processing-able format in China.
Key wordsClassification scheme      SKOS      Scheme framework      OWL     
Received: 25 April 2011      Published: 15 August 2011



Cite this article:

He Lin, Du Huiping. Review on Converting Enumerative Classification Schemes to SKOS. New Technology of Library and Information Service, 2011, 27(6): 79-84.

URL:     OR

[1] SKOS Simple Knowledge Organization System Primer[EB/OL].[2011-03-06].

[2] SWAD-Europe: Semantic Web Applications-Analysis and Selection[EB/OL].[2010-11-02].

[3] Dewey Decimal Classification-Linked Data[EB/OL].[2010-12-21].

[4] Panzer M, Zeng M L. Modeling Classification Systems in SKOS: Some Challenges and Best-Practice Recommendations[C/OL].[2011-03-06]. In: Proceedings of DC2009, Seoul, Korea. http://dcpapers.

[5] Zeng M L, Panzer M, Salaba A. Expressing Classification Schemes with OWL 2 Web Ontology Language—Issues and Opportunities[C]. In: Proceedings of the 11th International Conference of the International Society for Knowledge Organization (ISKO) 2010. 2010:356-362.

[6] 张士男,宋文.《科图法》SKOS描述方案设计[J]. 现代图书情报技术,2010(6):7-11.

[7] 喻非. 《中国分类主题词表》网络化研究:从MARC 到SKOS[C]. 见:网络环境下信息组织的创新与发展:全国第五次情报检索语言发展方向研讨会论文集. 北京:国家图书馆出版社,2009:139-147.

[8] 刘丽斌,张寿华,濮德敏,等.《中国分类主题词表》的SKOS描述自动转换研究[J].中国图书馆学报,2009,35(6):56-60.

[9] Zeng M L, Fan W. SKOS and Its Application in Transferring Traditional Thesauri into Networked Knowledge Organization Systems[EB/OL].[2011-03-06].

[10] SKOS Simple Knowledge Organization System Reference[EB/OL].[2011-02-06].

[11] 马张华,侯汉清, 薛春香. 文献分类法主题法导论(修订版)[M]. 北京:国家图书馆出版社,2009:90-91.

[12] 段荣婷.基于简约知识组织系统的《中国档案主题词表》语义网络化应用研究[J].现代图书情报技术,2010(10):34-42.

[13] Panzer M.DDC,SKOS and Linked Data on the Web[EB/OL].[2011-03-21].

[14] OWL 2 Web Ontology Language Structural Specification and Functional-Style Syntax[EB/OL].[2011-01-02].

[15] 侯汉清,刘华梅,郝嘉树.60来情报检索语言及其互操作进展(1949-2009)[J].图书馆杂志,2009,28(12):2-13.

[16] Soergel D, Lauser B, Liang A, et al. Reengineering Thesauri for New Applications: The AGROVOC Example[J/OL].[2010-12-20]. Journal of Digital Information, 2004,4(4).

[17] De Bruijn J, Hepp M. GenTax: A Generic Methodology for Deriving OWL and RDF-S Ontologies from Hierarchical Classifications, Thesauri, and Inconsistent Taxonomies[C]. In: Proceedings of the 4th European Semantic Web Conference (ESWC 2007), Innsbruck, Austria. Springer LNCS,2007,4519:129-144.
[1] Li Wenna,Zhang Zhixiong. Research on Knowledge Base Error Detection Method Based on Confidence Learning[J]. 数据分析与知识发现, 2021, 5(9): 1-9.
[2] Lu Yunmeng,Liu Tiezhong. Diffusion Model for Tacit Knowledge of Scientific Cooperation Network Based on Relevance: Case Study of Major Sci-Tech Projects[J]. 数据分析与知识发现, 2021, 5(9): 10-20.
[3] Zhou Yang,Li Xuejun,Wang Donglei,Chen Fang,Peng Lijuan. Visualizing Knowledge Graph for Explosive Formula Design[J]. 数据分析与知识发现, 2021, 5(9): 42-53.
[4] Shan Xiaohong,Wang Chunwen,Liu Xiaoyan,Han Shengxi,Yang Juan. Identifying Lead Users in Open Innovation Community from Knowledge-based Perspectives[J]. 数据分析与知识发现, 2021, 5(9): 85-96.
[5] Chai Qingfeng, Shi Linyan, Mei Shan, Xiong Haitao, He Huixin. Extracting Knowledge Elements of Sci-Tech Literature Based on Artificial and Machine Features[J]. 数据分析与知识发现, 2021, 5(8): 132-144.
[6] Shen Kejie, Huang Huanting, Hua Bolin. Constructing Knowledge Graph with Public Resumes[J]. 数据分析与知识发现, 2021, 5(7): 81-90.
[7] Ruan Xiaoyun,Liao Jianbin,Li Xiang,Yang Yang,Li Daifeng. Interpretable Recommendation of Reinforcement Learning Based on Talent Knowledge Graph Reasoning[J]. 数据分析与知识发现, 2021, 5(6): 36-50.
[8] Lu Linong,Zhu Zhongming,Zhang Wangqiang,Wang Xiaochun. Cross-database Knowledge Integration and Fingerprint of Institutional Repositories with Lingo3G Clustering Algorithm[J]. 数据分析与知识发现, 2021, 5(5): 127-132.
[9] Li He,Liu Jiayu,Li Shiyu,Wu Di,Jin Shuaiqi. Optimizing Automatic Question Answering System Based on Disease Knowledge Graph[J]. 数据分析与知识发现, 2021, 5(5): 115-126.
[10] Dai Bing,Hu Zhengyin. Review of Studies on Literature-Based Discovery[J]. 数据分析与知识发现, 2021, 5(4): 1-12.
[11] Shi Xiang,Liu Ping. Extraction and Representation of Domain Knowledge with Semantic Description Model and Knowledge Elements——Case Study of Information Retrieval[J]. 数据分析与知识发现, 2021, 5(4): 123-133.
[12] Li Ming, Li Ying, Zhou Qing, Wang Jun. Analyzing Knowledge Demand and Supply of Community Question Answering with TF-PIDF[J]. 数据分析与知识发现, 2021, 5(2): 106-115.
[13] Yu Chuanming, Zhang Zhengang, Kong Lingge. Comparing Knowledge Graph Representation Models for Link Prediction[J]. 数据分析与知识发现, 2021, 5(11): 29-44.
[14] Hua Bin, Wu Nuo, He Xin. Integrating Expert Reviews for Government Information Projects with Knowledge Fusion[J]. 数据分析与知识发现, 2021, 5(10): 124-136.
[15] Chen Shiji, Qiu Junping, Yu Bo. Topic Analysis of LIS Big Data Research with Overlay Mapping[J]. 数据分析与知识发现, 2021, 5(10): 51-59.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938