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http://dx.doi.org/10.9708/jksci.2020.25.10.023

Automatic Construction of SHACL Schemas for RDF Knowledge Graphs Generated by Direct Mappings  

Choi, Ji-Woong (School of Computer Science and Engineering, Soongsil University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.10, 2020 , pp. 23-34 More about this Journal
Abstract
In this paper, we proposes a method to automatically construct SHACL schemas for RDF knowledge graphs(KGs) generated by Direct Mapping(DM). DM and SHACL are all W3C recommendations. DM consists of rules to transform the data in an RDB into an RDF graph. SHACL is a language to describe and validate the structure of RDF graphs. The proposed method automatically translates the integrity constraints as well as the structure information in an RDB schema into SHACL. Thus, our SHACL schemas are able to check integrity instead of RDBMSs. This is a consideration to assure database consistency even when RDBs are served as virtual RDF KGs. We tested our results on 24 DM test cases, published by W3C. It was shown that they are effective in describing and validating RDF KGs.
Keywords
Knowledge graph; RDF; SHACL; Direct Mapping; RDF validation;
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1 E. Jimenez-Ruiz, E. Kharlamov, D. Zheleznyakov, I. Horrocks, C. Pinkel, M. G. Skjaeveland, E. Thorstensen, and J. Mora, "BootOX: Practical Mapping of RDBs to OWL 2," The Semantic Web - ISWC 2015, pp. 113-132, Bethlehem, USA, October 2015. DOI: 10.1007/978-3-319-25010-6_7
2 M. R. A. Rashid, G. Rizzo, M. Torchiano, N. Mihindukulasooriya, O. Corcho, and R. Garcia-Castro, "Completeness and consistency analysis for evolving knowledge bases," Journal of Web Semantics, Vol 54, pp. 48-71, January 2019. DOI: 10.1016/j.websem.2018.11.004.   DOI
3 M. O'Connor and A. Das, "SQWRL: a query language for OWL," Proceedings of the 6th International Conference on OWL: Experiences and Directions - Volume 529, pp. 208-215, Chantilly, USA, October 2009. DOI: 10.5555/2890046.2890072
4 I. Kollia, B. Glimm, and I. Horrocks, "SPARQL Query Answering over OWL Ontologies," Proceedings of the 8th Extended Semantic Web Conference on The Semantic Web: Research and Applications - Volume Part I, pp. 382-396, Heraklion, Greece, May 2011. DOI: 10.1007/978-3-642-21034-1_26
5 E. Sirin and B. Parsia, "SPARQL-DL: SPARQL Query for OWL-DL," Proceedings of the OWLED 2007 Workshop on OWL: Experiences and Directions, Innsbruck, Austria, June 2007.
6 D. Peterson, S. Gao, A. Malhotra, C. M. Sperberg-McQueen, and H. S. Thompson, "W3C XML Schema Definition Language (XSD) 1.1 Part 2: Datatypes," http://www.w3.org/TR/xmlschema11-2/
7 B. Villazon-Terrazas and M. Hausenblas, "R2RML and Direct Mapping Test Cases," https://www.w3.org/TR/rdb2rdf-test-cases/
8 J. E. L. Gayo, H. Knublauch and D. Kontokostas, "SHACL Test Suite and Implementation Report," https://w3c.github.io/data-shapes/data-shapes-test-suite/
9 Q. Xu, X. Wang, J. Li, Q. Zhang, and L. Chai, "Distributed Subgraph Matching on Big Knowledge Graphs Using Pregel," IEEE Access, Vol. 7, pp. 116453-116464, August 2019. DOI: 10.1109/ACCESS.2019.2936465   DOI
10 H. Paulheim, "Knowledge graph refinement: A survey of approaches and evaluation methods," Semantic Web, Vol. 8, No. 3, pp. 489-508, Dec. 2017. DOI: 10.3233/SW-160218   DOI
11 D. Buscaldi, D. Dess, E. Motta, F. Osborne, and D. R. Recupero, "Mining scholarly data for fine-grained knowledge graph construction," Proceedings of the Workshop on Deep Learning for Knowledge Graphs Co-located with the 16th Extended Semantic Web Conference 2019, pp. 21-30, Portoroz, Slovenia, June, 2019.
12 H. Arnaout and S. Elbassuoni, "Effective searching of RDF knowledge graphs," Journal of Web Semantics, Vol. 48, pp. 66-84, Jan. 2018. DOI: 10.1016/j.websem.2017.12.001   DOI
13 J. Z. Pan, G. Vetere, J. M. Gomez-Perez, and H. Wu, "Exploiting Linked Data and Knowledge Graphs in Large Organisations," Springer, Cham, pp. 147-180, 2017.
14 W. Zheng, L. Zou, W. Peng, X. Yan, S. Song, and D. Zhao, "Semantic SPARQL similarity search over RDF knowledge graphs," Proceedings of the VLDB Endowment, Vol. 9, No. 11, pp. 840-851, July 2016. DOI: 10.14778/2983200.2983201   DOI
15 H. Knublauch and D. Kontokostas, "Shapes Constraint Language (SHACL)," https://www.w3.org/TR/shacl/
16 H. Paulheim, "Machine Learning with and for Semantic Web Knowledge Graphs," Reasoning Web. Learning, Uncertainty, Streaming, and Scalability, pp 110-141, Esch-sur-Alzette, Luxembourg, September, 2018. DOI: 10.1007/978-3-030-00338-8_5.
17 O. Corcho, F. Priyatna and D. Chaves-Fraga, "Towards a New Generation of Ontology Based Data Access," Semantic Web, Vol. 11, No. 1, pp. 153-160, January 2020. DOI: 10.3233/SW-190384   DOI
18 M. Arenas, A. Bertails, E. Prud'hommeaux, and J. Sequeda, "A Direct Mapping of Relational Data to RDF," http://www.w3.org/TR/rdb-direct-mapping/
19 S. Das, S. Sundara, and R. Cyganiak, "R2RML: RDB to RDF Mapping Language," http://www.w3.org/TR/r2rml/
20 G. Xiao, L. Ding, B. Cogrel, and D. Calvanese, "Virtual Knowledge Graphs: An overview of systems and use cases," Data Intelligence, vol. 1, no. 3, pp. 201-223, May, 2019. DOI: 10.1162/dint_a_00011   DOI
21 B. Motik, P. F. Patel-Schneider, and B. Parsia, "OWL 2 Web Ontology Language Structural Specification and Functional-Style Syntax (Second Edition)," http://www.w3.org/TR/owl-syntax/
22 J. F. Sequeda, M. Arenas, and D. P. Miranker, "On directly mapping relational databases to RDF and OWL," Proceedings of the 21st international conference on World Wide Web, pp. 649-658, Lyon, France, April 2012. DOI: 10.1145/2187836.2187924