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An Approach for Automatically Generating R2RML-Based Direct Mapping from Relational Databases

  • Conference paper
  • First Online:
Social Computing (ICYCSEE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 623))

Abstract

For integrating relational databases (RDBs) into semantic web applications, the W3C RDB2RDF Working Group recommended two approaches, Direct Mapping (DM) and R2RML. The DM provides a set of mapping rules according to RDB schema, while the R2RML allows users to manually define mappings according to existing target ontology. The major problem to use R2RML is the effort for creating R2RML mapping documents manually. This may lead to appearance of many mistakes in the R2RML documents and requires domain experts. In this paper, we propose and implement an approach to generate an R2RML mapping documents automatically from RDB schema. The R2RML mapping reflects the behavior of the DM specification and allows any R2RML parser to generate a set of RDF triples from relational data. The input of generating approach is DBsInfo class that automatically generated from relational schema. An experimental prototype is developed and shows the effectiveness of our approach algorithms.

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Notes

  1. 1.

    https://metacpan.org/release/RDF-RDB2RDF.

  2. 2.

    https://bitbucket.org/r2rml4net/core/wiki/Home.

  3. 3.

    https://github.com/antidot/db2triples.

  4. 4.

    http://www.antidot.net/.

  5. 5.

    https://github.com/nkons/r2rml-parser.

  6. 6.

    http://d2rq.org/example/iswc-mysql.sql.

  7. 7.

    http://www.artfulsoftware.com/mysqlbook/sampler/mysqled1_appe.html#5-1.

  8. 8.

    http://mysql-tools.com/en/downloads/mysql-databases/4-sakila-db.html.

  9. 9.

    https://code.google.com/p/northwindextended/downloads/detail?name=Northwind.MySQL5.sql.

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Acknowledgments

This work is supported by National Natural Science Foundation of China under grants 61572221, 61173170, 61300222, 61370230, 61433006 and U1401258, Innovation Fund of Huazhong University of Science and Technology under grants 2015TS069 and 2015TS071, Science and Technology Support Program of Hubei Province under grant 2014BCH270 and 2015AAA013, and Science and Technology Program of Guangdong Province under grant 2014B010111007.

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Mohamed A. G. Hazber & Ruixuan Li

  2. Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia

    Guandong Xu

  3. Computer Science, IBB University, Ibb, Yemen

    Khaled M. Alalayah

  4. Computer Science, Najran University-Sharurah, Najran, Saudi Arabia

    Khaled M. Alalayah

Authors
  1. Mohamed A. G. Hazber
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  2. Ruixuan Li
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  3. Guandong Xu
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  4. Khaled M. Alalayah
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Corresponding author

Correspondence to Ruixuan Li .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology , Harbin, China

    Wanxiang Che

  2. Harbin Engineering University , Harbin, China

    Qilong Han

  3. Harbin Institute of Technology , Harbin, China

    Hongzhi Wang

  4. Northeast Forestry University , Harbin, China

    Weipeng Jing

  5. National University of Defense Technology , Changsha, China

    Shaoliang Peng

  6. Harbin Engineering University , Harbin, China

    Junyu Lin

  7. Harbin Univ. of Science and Technology , Harbin, China

    Guanglu Sun

  8. Harbin Univ. of Science and Technology , Harbin, China

    Xianhua Song

  9. Harbin Engineering University , Harbin, China

    Hongtao Song

  10. Harbin Sea of Clouds & Computer Tech. , Harbin, China

    Zeguang Lu

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Hazber, M.A.G., Li, R., Xu, G., Alalayah, K.M. (2016). An Approach for Automatically Generating R2RML-Based Direct Mapping from Relational Databases. In: Che, W., et al. Social Computing. ICYCSEE 2016. Communications in Computer and Information Science, vol 623. Springer, Singapore. https://doi.org/10.1007/978-981-10-2053-7_15

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  • DOI: https://doi.org/10.1007/978-981-10-2053-7_15

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  • Online ISBN: 978-981-10-2053-7

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