Mapping of extensible markup language-to-ontology representation for effective data integration

Q2 Decision Sciences
S. Haw, Lit-Jie Chew, D. S. Kusumo, P. Naveen, Kok-Why Ng
{"title":"Mapping of extensible markup language-to-ontology representation for effective data integration","authors":"S. Haw, Lit-Jie Chew, D. S. Kusumo, P. Naveen, Kok-Why Ng","doi":"10.11591/ijai.v12.i1.pp432-442","DOIUrl":null,"url":null,"abstract":"Extensible markup language (XML) is well-known as the standard for data exchange over the Internet. It is flexible and has high expressibility to express the relationship between the data stored. Yet, the structural complexity and the semantic relationships are not well expressed. On the other hand, ontology models the structural, semantic and domain knowledge effectively. By combining ontology with visualization effect, one will be able to have a closer view based on respective user requirements. In this paper, we propose several mapping rules for the transformation of XML into ontology representation. Subsequently, we show how the ontology is constructed based on the proposed rules using the sample domain ontology in University of Wisconsin-Milwaukee (UWM) and mondial datasets. We also look at the schemas, query workload, and evaluation, to derive the extended knowledge from the existing ontology. The correctness of the ontology representation has been proven effective through supporting various types of complex queries in simple protocol and resource description framework query language (SPARQL) language.","PeriodicalId":52221,"journal":{"name":"IAES International Journal of Artificial Intelligence","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IAES International Journal of Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijai.v12.i1.pp432-442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

Extensible markup language (XML) is well-known as the standard for data exchange over the Internet. It is flexible and has high expressibility to express the relationship between the data stored. Yet, the structural complexity and the semantic relationships are not well expressed. On the other hand, ontology models the structural, semantic and domain knowledge effectively. By combining ontology with visualization effect, one will be able to have a closer view based on respective user requirements. In this paper, we propose several mapping rules for the transformation of XML into ontology representation. Subsequently, we show how the ontology is constructed based on the proposed rules using the sample domain ontology in University of Wisconsin-Milwaukee (UWM) and mondial datasets. We also look at the schemas, query workload, and evaluation, to derive the extended knowledge from the existing ontology. The correctness of the ontology representation has been proven effective through supporting various types of complex queries in simple protocol and resource description framework query language (SPARQL) language.
可扩展标记语言到本体表示的映射,以实现有效的数据集成
可扩展标记语言(XML)作为Internet上数据交换的标准而闻名。它灵活,表达存储的数据之间的关系具有很高的可表达性。然而,其结构复杂性和语义关系没有得到很好的表达。另一方面,本体对结构知识、语义知识和领域知识进行了有效的建模。通过将本体与可视化效果相结合,可以根据各自的用户需求有一个更近的视图。本文提出了将XML转换为本体表示的几种映射规则。随后,我们使用威斯康星大学密尔沃基分校(UWM)的样本领域本体和mondial数据集展示了如何基于提出的规则构建本体。我们还将查看模式、查询工作负载和评估,以便从现有本体派生扩展的知识。通过简单协议和资源描述框架查询语言(SPARQL)语言支持各种类型的复杂查询,证明了本体表示的正确性是有效的。
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
IAES International Journal of Artificial Intelligence
IAES International Journal of Artificial Intelligence Decision Sciences-Information Systems and Management
CiteScore
3.90
自引率
0.00%
发文量
170
×
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:481959085
Book学术官方微信