EM3B2 – a semantic integration engine for materials science

Author:

Zhao Chongchong,Dong Chao,Zhang Xiaoming

Abstract

Purpose – The integration and retrieval of the vast data have attracted sufficient attention, thus the W3C workgroup releases R2RML to standardize the transformation from relational data to semantic-aware data. However, it only provides a data transform mechanism to resource description framework (RDF). The generation of mapping alignments still needs manual work or other algorithms. Therefore, the purpose of this paper is to propose a domain-oriented automatic mapping method and an application of the R2RML standard. Design/methodology/approach – In this paper, materials science is focussed to show an example of domain-oriented mapping. source field concept and M3B2 (Metal Materials Mapping Background Base) knowledge bases are established to support the auto-recommending algorithm. As for the generation of RDF files, the idea is to generate the triples and the links, respectively. The links of the triples follow the object-subject relationship, and the links of the object properties can be achieved by the range individuals and the trail path. Findings – Consequently based on the previous work, the authors proposed Engine for Metal Materials Mapping Background Base (EM3B2), a semantic integration engine for materials science. EM3B2 not only offers friendly graphical interfaces, but also provides auto-recommending mapping based on materials knowledge to enable users to avoid vast manually work. The experimental result indicates that EM3B2 supplies accurate mapping. Moreover, the running time of E3MB2 is also competitive as classical methods. Originality/value – This paper proposed EM3B2 semantic integration engine, which contributes to the relational database-to-RDF mapping by the application of W3C R2RML standard and the domain-oriented mapping.

Publisher

Emerald

Subject

Library and Information Sciences,Information Systems

Reference41 articles.

1. Ashino, T. (2010), “Materials ontology: an infrastructure for exchanging materials information and knowledge”, DataScience Journal , Vol. 9 No. 1, pp. 54-61.

2. Astrova, I. , Korda, N. and Kalja, A. (2007), “Rule-based transformation of sql relational databases to owl ontologies”, Proceedings of the 2nd International Conference on Metadata & Semantics Research, pp. 213-216.

3. Berners-Lee, T. (2001), “The semantic web”, Scientific American , Vol. 284 No. 5, pp. 34-43.

4. Bertails, A. , Arenas, M. , Prud’hommeaux, E. and Sequeda, J. (2013), “A direct mapping of relational data to RDF”, available at: www.w3.org/TR/rdb-direct-mapping/ (accessed November 19, 2013).

5. Bizer, C. and Seaborne, A. (2004), “D2RQ-treating non-RDF databases as virtual RDF graphs”, Proceeings of 3rd International Semantic Web Conference, pp. 457-460.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3