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http://dx.doi.org/10.9708/jksci.2022.27.11.067

Automatic Creation of ShEx Schemas for RML-Based RDF Knowledge Graph Validation  

Choi, Ji-Woong (School of Computer Science and Engineering, Soongsil University)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.11, 2022 , pp. 67-80 More about this Journal
Abstract
In this paper, we propose a system which automatically generates the ShEx schemas to describe and validate RDF knowledge graphs constructed by RML mapping. ShEx schemas consist of constraints. The proposed system generates most of the constraints by converting the RML mapping rules. The schemas consisting only of constraints obtained from mapping rules can help users to figure out the structure of the graphs generated by RML mapping, but they are not sufficient for sophisticated validation purposes. For users who need a schema for validation, the proposed system is also able to provide the schema with added constraints generated from metadata extracted from the input data sources for RML mapping. The proposed system has the ability to handle CSV, XML, JSON or RDBMS as input data sources. Testing results from 297 cases show that the proposed system can be applied for RDF graph validation in various practical cases.
Keywords
RML; ShEx; RDF; Knowledge Graph; Validation;
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1 R. B. Thapa, and M. Giese, "A Source-to-Target Constraint Rewriting for Direct Mapping," Proceedings of 20th International Semantic Web Conference, pp. 21-38, Virtual Event, October 2021. DOI: 10.1007/978-3-030-88361-4_2   DOI
2 S. Das, S. Sundara, and R. Cyganiak, R2RML: RDB to RDF Mapping Language, http://www.w3.org/TR/r2rml/
3 K. Rabbani, M. Lissandrini, and K. Hose, "SHACL and ShEx in the Wild: A Community Survey on Validating Shapes Generation and Adoption," Companion Proceedings of the Web Conference 2022 (WWW '22 Companion), pp. 260-263, Lyon, France, April 2022. DOI: 10.1145/3487553.3524253   DOI
4 J. E. L. Gayo, E. Prud'hommeaux, I. Boneva, and D. Kontokostas, "Validating RDF Data," Springer Nature, pp. 233-266, 2022.
5 E. Prud'hommeaux, I. Boneva, J. E. L. Gayo, and G. Kellogg, Shape Expressions Language 2.1, https://shex.io/shex-semantics/index.html
6 H. Knublauch, and D. Kontokostas, Shapes Constraint Language (SHACL), http://www.w3.org/TR/shacl/
7 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/
8 S. Harris, and A. Seaborne, SPARQL 1.1 Query Language, http://www.w3.org/TR/sparql11-query/
9 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/
10 M. Sporny, D. Longley, G. Kellogg, M. Lanthaler, P. Champin, and N. Lindstrom, JSON-LD 1.1, http://www.w3.org/TR/json-ld11/
11 G. Carothers, RDF 1.1 N-Quads, https://www.w3.org/TR/n-quads/
12 A. Hogan, E. Blomqvist, M. Cochez, C. D'amato, G. D. Melo, C. G., S. Kirrane, J. E. L. Gayo, R. Navigli, S. Neumaier, A. N. Ngomo, A. Polleres, S. M. Rashid, A. Rula, L. Schmelzeisen, J. Sequeda, S. Staab, and A. Zimmermann, "Knowledge Graphs," ACM Computing Surveys, Vol. 54, No. 71, pp. 1-37, May 2022. DOI: 10.1145/3447772   DOI
13 J. Choi, "Automatic Construction of SHACL Schemas for RDF Knowledge Graphs Generated by Direct Mappings," Journal of the Korea Society of Computer and Information Vol. 25, No. 10, pp. 23-34, October 2020. DOI: 10.9708/JKSCI.2020.25.10.023   DOI
14 D. Beckett, T. Berners-Lee, E. Prud'hommeaux, and G. Carothers, RDF 1.1 Turtle, https://www.w3.org/TR/turtle/
15 D. Fernandez-Alvarez, J. E. Labra-Gayo, and D. Gayo-Avello, "Automatic extraction of shapes using sheXer," Knowledge-Based Systems, Vol. 238, No. 107975, pp. 1-9, February 2022. DOI:10.1016/j.knosys.2021.107975   DOI
16 I. Boneva, J. Lozano, and S. Staworko, "Relational to RDF Data Exchange in Presence of a Shape Expression Schema," Proceedings of the 12th Alberto Mendelzon International Workshop on Foundations of Data Management, pp. 1-16, Cali, Colombia, May 2018. DOI: 10.48550/arXiv.1804.11052   DOI
17 J. Choi, "ShEx Schema Generator for RDF Graphs Created by Direct Mapping," Journal of the Korea Society of Computer and Information Vol. 23, No. 10, pp. 33-43, October 2018. DOI:10.9708/JKSCI.2018.23.10.033   DOI
18 J. Choi, "Automatic Construction of SHACL Schemas for RDF Knowledge Graphs Generated by R2RML Mappings," Journal of the Korea Society of Computer and Information Vol. 25, No. 8, pp. 9-21, August 2020. DOI: 10.9708/JKSCI.2020.25.08.009   DOI
19 J. Choi, "R2RML Based ShEx Schema," Journal of the Korea Society of Computer and Information Vol. 23, No. 10, pp. 45-55, October 2018. DOI: 10.9708/JKSCI.2018.23.10.045   DOI
20 P. Heyvaert, A. Dimou and B. D. Meester, RML Test Cases, https://rml.io/test-cases/
21 R. Waterson, Build a knowledge graph in Amazon Neptune using Data Lens, https://aws.amazon.com/blogs/database/build-a-knowledge-graph-in-amazon-neptune-using-data-lens/
22 A. Dimou, "High-quality knowledge graphs generation: R2rml and rml comparison, rules validation and inconsistency resolution," Applications and Practices in Ontology Design, Extraction, and Reasoning, Vol. 49, No. 4, pp. 55-72, November 2020. DOI: 10.3233/SSW200035   DOI
23 V. Janev, D. Graux, H. Jabeen, and E. Sallinger, "Knowledge Graphs and Big Data Processing," Springer Cham, pp. 59-72, July 2020.
24 I. Boneva, J. Lozano, and S. Staworko, "Consistency and Certain Answers in Relational to RDF Data Exchange with Shape Constraints," Proceedings of New Trends in Databases and Information Systems, pp. 97-107, Lyon, France, August 2020. DOI: 10.1007/978-3-030-54623-6_9   DOI
25 T. Delva, B. D. Smedt, S. M. Oo, D. V. Assche, S. Lieber, and A. Dimou, "RML2SHACL: RDF Generation Is Shaping Up," Proceedings of the 11th on Knowledge Capture Conference (K-CAP '21), pp. 153-160, New York, USA, December 2021. DOI: 10.1145/3460210.3493562Q   DOI
26 N. Noy, Y. Gao, A. Jain, A. Narayanan, A. Patterson, and J. Taylor, "Industry-Scale Knowledge Graphs: Lessons and Challenges," Communications of the ACM, Vol. 62, No. 8, pp. 36-43, August 2019. DOI: 10.1145/3331166   DOI
27 Y. Leng, H. Wang and F. Lu, "Artificial Intelligence Knowledge Graph for Dynamic Networks: An Incremental Partition Algorithm," IEEE Access, Vol. 8, pp. 63434-63442, March 2020. DOI: 10.1109/ACCESS.2020.2982652   DOI