Tools for mapping ontologies to relational databases: A comparative evaluation

Dorin Moldovan, Marcel Antal, D. Valea, Claudia Pop, T. Cioara, I. Anghel, I. Salomie
{"title":"Tools for mapping ontologies to relational databases: A comparative evaluation","authors":"Dorin Moldovan, Marcel Antal, D. Valea, Claudia Pop, T. Cioara, I. Anghel, I. Salomie","doi":"10.1109/ICCP.2015.7312609","DOIUrl":null,"url":null,"abstract":"This paper presents an analysis of the state of the art solutions for mapping a relational database and an ontology by adding reasoning capabilities and offering the possibility to query the inferred information. We analyzed four approaches: Jena with D2RQ, Jena with R2RML, KAON2 and OWL API. In order to highlight the differences between the four approaches, we used a nutrition diagnostics related ontology for the definition of the concepts and of the rules, and a relational database for the storage of the individuals. As performance evaluation, we focused on the time required to map the relational database to the ontology, and the time required to retrieve the information that is inferred about the diagnostics of a number of people. The obtained results show that the best performance in both cases is given by KAON2.","PeriodicalId":158453,"journal":{"name":"2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCP.2015.7312609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

This paper presents an analysis of the state of the art solutions for mapping a relational database and an ontology by adding reasoning capabilities and offering the possibility to query the inferred information. We analyzed four approaches: Jena with D2RQ, Jena with R2RML, KAON2 and OWL API. In order to highlight the differences between the four approaches, we used a nutrition diagnostics related ontology for the definition of the concepts and of the rules, and a relational database for the storage of the individuals. As performance evaluation, we focused on the time required to map the relational database to the ontology, and the time required to retrieve the information that is inferred about the diagnostics of a number of people. The obtained results show that the best performance in both cases is given by KAON2.
将本体映射到关系数据库的工具:比较评价
本文通过增加推理能力和提供查询推断信息的可能性,分析了映射关系数据库和本体的最新解决方案。我们分析了四种方法:Jena与D2RQ, Jena与R2RML, KAON2和OWL API。为了突出这四种方法之间的差异,我们使用营养诊断相关的本体来定义概念和规则,并使用关系数据库来存储个体。作为性能评估,我们关注的是将关系数据库映射到本体所需的时间,以及检索关于许多人的诊断推断的信息所需的时间。结果表明,KAON2在这两种情况下都具有最佳的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信