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New Technology of Library and Information Service  2009, Vol. 25 Issue (7-8): 1-5    DOI: 10.11925/infotech.1003-3513.2009.07-08.01
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Practice of Creating and Reasoning Science Ontology by Protégé
Hong Na1,2  Zhang Zhixiong1
1(National Science Library, Chinese Academy of Sciences, Beijing 100190, China)
2(Graduate University of Chinese Academy of Sciences, Beijing 100049, China)
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Abstract  

 After analyzing and using the Ontology editor Protégé, this paper chooses science individuals which extracting from Web content as analysis objects, and  tries out an experiment on creating science Ontology and reasoning on a simple relation. This paper also explains these methods and examples. Finally, it sums up some problems still existing in large scale Ontology storage and management.
Key words： Protégé      Ontology      Individual      Reason     
Received: 31 March 2009      Published: 25 August 2009
ZTFLH: 

G250.76

 		 
Corresponding Authors: Hong Na     E-mail: hongn@mail.las.ac.cn
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Cite this article:

Hong Na,Zhang Zhixiong. Practice of Creating and Reasoning Science Ontology by Protégé. New Technology of Library and Information Service, 2009, 25(7-8): 1-5.

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http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2009.07-08.01     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2009/V25/I7-8/1

［1］ Protégé［EB/OL］.［2009-03-01］. http://protege.stanford.edu.
［2］ Ettorre M, Pontieri P, Ruffolo M, et al. A Prototypal Environment for Collaborative Work Within a Research Organization［C］. In: Proceedings of the 14th International Workshop on Database and Expert Systems Applications,Ithaca,Greece.2003:274.
［3］ Protégé-OWL API Programmer’s Guide［EB/OL］.［2009-03-01］. http://protege.stanford.edu/plugins/owl/api/guide.html.
［4］ Using the Protégé-OWL Reasoner API ［EB/OL］.［2009-03-01］. http://protege.stanford.edu/plugins/owl/api/ReasonerAPIExamples.html.
［5］ RacerPro［EB/OL］.［2009-03-01］.http://www.racer-systems.com/.
［6］ Jena 2 Inference Support［EB/OL］.［2009-03-01］. http://jena.sourceforge.net/inference/.
［7］ Lu J, Ma L,  Zhang L, et al.  SOR: A Practical System for Ontology Storage, Reasoning and Search［C］. In:Proceedings of the 33rd International Conference on Very Large Data Bases, Vienna, Austria.2007: 1402-1405.
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