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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (10): 77-84    DOI: 10.11925/infotech.2096-3467.2017.0366
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Analyzing owl:sameAs Network in Linked Data
Jia Junzhi(), Li Xiao
School of Economics and Management, Shanxi University, Taiyuan 030006, China
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Abstract  

[Objective] This paper examines the application of the owl:sameAs link in the Web of Data. [Methods] First, we extracted owl:sameAs links from the BTC 2014 dataset. Then, we analyzed the structure of the sample data, as well as their domain names and instance types. [Results] The retrieved links of owl:sameAs were sparse, and most entities only had single connection between each other. [Limitations] The size of our sample data was small, and more comprehensive analysis was needed. [Conclusions] Our study lays some foundations for data integration, ontology alignment, knowledge discovery of the Web of Data.

Key wordsowl:sameAs      Interlinking of Datasets      Network     
Received: 05 May 2017      Published: 08 November 2017
ZTFLH:  G254  

Cite this article:

Jia Junzhi,Li Xiao. Analyzing owl:sameAs Network in Linked Data. Data Analysis and Knowledge Discovery, 2017, 1(10): 77-84.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.0366     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I10/77

谓词缩写 谓词URI及备注 数量
rdf:type <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> 定义实例和类之间的联系 64 449
owl:sameAs <http://www.w3.org/2002/07/owl#sameAs> 表示由不同URI标识的两个RDF资源指的是同一个对象 44 746
skos:exactMatch <http://www.w3.org/2004/02/skos/core#exactMatch> 连接两个有足够的可信度并在信息检索应用程序较大范围可以交替使用的概念, 是skos:closeMatch的子属性 13 102
rdfs:seeAlso <http://www.w3.org/2000/01/rdf-schema#seeAlso> 将一个资源关联到另一个解释它的资源 5 570
skos:closeMatch <http://www.w3.org/2004/02/skos/core#closeMatch> 连接两个足够相似以致在一些信息检索应用程序可以交替使用的概念 1 490
dcterms:type <http://purl.org/dc/terms/type> 描述文件格式、物理媒介或资源的维度 1 170
sameAs谓词 数量 占比
<http://www.w3.org/2002/07/owl#sameAs> 44 746 97.60%
<http://www.w3.org/2000/01/rdf-schema#sameAs> 631 1.38%
<owl:sameAs> 445 0.97%
<htpp://www.abes.fr/owlsameAs> 16 0.03%
<http://lexvo.org/ontology#nearlySameAs> 4 0.009%
<http://linkedgeodata.org/ontology/gadmSameAs> 4 0.009%
源数据集 目标数据集 基于owl:sameAs连接的最常用的type对
源数据集type 目标数据集type
theses.fr idref.fr <http://www.abes.fr/foafPerson> <http://xmlns.com/foaf/0.1/Person>
<http://www.abes.fr/foafAgent> <http://xmlns.com/foaf/0.1/Person>
<http://www.abes.fr/foafAgent> <http://xmlns.com/foaf/0.1/Organization>
d-nb.info dbpedia.org <http://d-nb.info/standards/elementset/gnd#
DifferentiatedPerson>
<http://dbpedia.org/class/yago/Traveler109629752>
morelab.deusto.es dblp.l3s.de <http://swrc.ontoware.org/ontology#Article> <http://purl.org/dc/dcmitype/Text>
wals.info glottolog.org <http://purl.org/dc/terms/LinguisticSystem> <http://purl.org/linguistics/gold/Language>
didactalia.net data.nytimes.com <http://rdfs.org/sioc/types#Tag> <http://www.w3.org/2004/02/skos/core#Concept>
[1] Bizer C, Tom H, Berners-Lee T, et al.Linked Data: The Story So Far[J]. International Journal on Semantic Web & Information Systems, 2009, 5(3): 1-22.
doi: 10.4018/jswis.2009081901
[2] Abele A, McCrae J. Linking Open Data Cloud Diagram 2017 [EB/OL]. [2017-03-07].
[3] Schmachtenberg M, Bizer C, Paulheim H.Adoption of the Linked Data Best Practices in Different Topical Domains[C]// Proceedings of the 13th International Semantic Web Conference. 2014: 245-260.
[4] Gunaratna K, Lalithsena S, Sheth A.Alignment and Dataset Identification of Linked Data in Semantic Web[J]. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2014, 4(2): 139-151.
doi: 10.1002/widm.1121
[5] Parundekar R, Knoblock C A, Ambite J L.Linking and Building Ontologies of Linked Data[C]// Proceedings of the 9th International Semantic Web Conference, Shanghai, China. 2010.
[6] Correndo G, Penta A, Gibbins N, et al.Statistical Analysis of the owl:sameAs Network for Aligning Concepts in the Linking Open Data Cloud[J]. Lecture Notes in Computer Science, 2012, 7447(5): 215-230.
doi: 10.1007/978-3-642-32597-7
[7] Nikolov A, Motta E.Capturing Emerging Relations Between Schema Ontologies on the Web of Data[C]//Proceedings of the 9th Semantic Web Conference, Shanghai, China. 2010.
[8] Gunaratna K, Thirunarayan K, Jain P, et al.A Statistical and Schema Independent Approach to Identify Equivalent Properties on Linked Data[C]// Proceedings of the 9th International Conference on Semantic Systems. ACM, 2013: 33-40.
[9] Bechhofer S, van Harmelen F, Hendler J, et al. OWL Web Ontology Language Reference. [EB/OL].[2016-11-02].
[10] 郭世泽, 陆哲明. 复杂网络基础理论[M]. 北京: 科学出版社, 2012.
[10] (Guo Shize, Lu Zheming.Basic Theory of Complex Networks [M].Beijing: Science Press, 2012.)
[11] Tobias K, Andreas H. Billion Triples Challenge 2014 Dataset [EB/OL]. [2016-10-11].
[12] Using owl:sameAs in Linked Data[EB/OL]. [2016-10-12].
[13] Auer S, Bizer C, Kobilarov G, et al.DBpedia: A Nucleus for a Web of Open Data[C]// Proceedings of the 6th International Semantic Web Conference on Semantic Web. 2007.
[14] Hotho A.BibSonomy: A Social Bookmark and Publication Sharing System[C]// Proceedings of the 14th International Conference on Conceptual Structures, Aalborg, Denmark. Aalborg University Press, 2006.
[15] EUscreen Linked Open Data Pilot [EB/OL]. [2017-03-08].
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