skip to main content
10.1145/3436829.3436855acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicsieConference Proceedingsconference-collections
research-article

Querying Heterogeneous Property Graph Data Sources based on a Unified Conceptual View

Published:05 January 2021Publication History

ABSTRACT

With the great success of NoSQL (Not only SQL) databases, data becomes more heterogeneous than ever. Hence, it is essential to provide solutions to integrate such heterogeneous databases and facilitate accessing them. This paper proposes an Ontology Based Data Access (OBDA) approach to query NoSQL property graph databases using SPARQL language. This allows users to access diverse data sources with the same query through a unified conceptual view (ontology). The proposed work goes through an offline phase to map the property graph data model to a unified ontology model. This is done by proposing hybrid relational graph algebra expressions. Then, an online phase starts when the user submits a SPARQL query. The submitted query is translated into the property graph declarative query language, Cypher. The translated query is then executed on the target property graph database and query results are presented to users in a unified format.

References

  1. Poggi, D. Lembo, D. Calvanese, G. De Giacomo, M. Lenzerini, and R. Rosati, "Linking Data to Ontologies," J. Data Semant. X, pp. 133--173, 2008.Google ScholarGoogle Scholar
  2. Brayner, M. Meirelles, and J. A. M. Filho, "Integrating heterogeneous data sources in the web," Université Côte d'Azur, 2017.Google ScholarGoogle Scholar
  3. R. Angles, H. Thakkar, and D. Tomaszuk, "RDF and Property Graphs Interoperability: Status and Issues," in Proceedings of the 13th Alberto Mendelzon International Workshop on Foundations of Data Management (AMW 2019), Asunción, Paraguay, 2019.Google ScholarGoogle Scholar
  4. J. Marton, G. Szárnyas, and D. Varró, "Formalising openCypher Graph Queries in Relational Algebra," in Advances in Databases and Information Systems, 2017, pp. 182--196.Google ScholarGoogle ScholarCross RefCross Ref
  5. S. Decker, P. Mitra, and S. Melnik, "Framework for the semantic Web: an RDF tutorial," IEEE Internet Comput., vol. 4, no. 6, pp. 68--73, 2000.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. "SPARQL Query Language for RDF." [Online]. Available: https://www.w3.org/TR/rdf-sparql-query/. [Accessed: 14-Mar-2019].Google ScholarGoogle Scholar
  7. F. Michel, L. Djimenou, C. Faron-Zucker, and J. Montagnat, "Translation of Heterogeneous Databases into RDF, and Application to the Construction of a SKOS Taxonomical Reference," in International Conference on Web Information Systems and Technologies, 2015, pp. 275--296.Google ScholarGoogle Scholar
  8. F. Michel, C. Faron-Zucker, and J. Montagnat, "Bridging the Semantic Web and NoSQL Worlds: Generic SPARQL Query Translation and Application to MongoDB," in Transactions on Large-Scale Data-and Knowledge-Centered Systems XL, Springer, 2019, pp. 125--165.Google ScholarGoogle ScholarCross RefCross Ref
  9. A. Chebotko, S. Lu, and F. Fotouhi, "Semantics preserving SPARQL-to-SQL translation," Data Knowl. Eng., vol. 68, no. 10, pp. 973--1000, 2009.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. F. Priyatna, O. Corcho, and J. Sequeda, "Formalisation and experiences of R2RML-based SPARQL to SQL query translation using morph," in Proceedings of the 23rd international conference on World wide web, 2014, pp. 479--490.Google ScholarGoogle Scholar
  11. M. Rodriguez-Muro and M. Rezk, "Efficient SPARQL-to-SQL with R2RML mappings," Web Semant. Sci. Serv. Agents World Wide Web, vol. 33, pp. 141--169, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  12. D. Calvanese et al., "Ontop: Answering SPARQL queries over relational databases," Semant. Web, vol. 8, no. 3, pp. 471--487, 2017.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. H. Abbes and F. Gargouri, "Big data integration: A MongoDB database and modular ontologies-based approach," Procedia Comput. Sci., vol. 96, pp. 446--455, 2016.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. E. Botoeva, D. Calvanese, B. Cogrel, M. Rezk, and G. Xiao, "OBDA beyond relational DBs: A study for MongoDB," 2016.Google ScholarGoogle Scholar
  15. N. C. Cysneiros and A. C. Salgado, "Including hierarchical navigation in a Graph Database query language with an OBDA approach," in Data Engineering Workshops (ICDEW), 2016 IEEE 32nd International Conference on, 2016, pp. 109--114.Google ScholarGoogle Scholar
  16. H. Thakkar, D. Punjani, J. Lehmann, and S. Auer, "Two for one: querying property graph databases using SPARQL via g remlinator," in Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 2018, p. 12.Google ScholarGoogle Scholar
  17. "Neo4j Graph Platform -- The Leader in Graph Databases." [Online]. Available: https://neo4j.com/. [Accessed: 14-Mar-2019].Google ScholarGoogle Scholar
  18. "neo4j-examples/neo4j-movies-template." [Online]. Available: https://github.com/neo4j-examples/neo4j-movies-template. [Accessed: 14-Mar-2019].Google ScholarGoogle Scholar
  19. "Turtle - Terse RDF Triple Language." [Online]. Available: https://www.w3.org/TR/turtle/. [Accessed: 14-Mar-2019].Google ScholarGoogle Scholar
  20. "ARQ - A SPARQL Processor for Jena." [Online]. Available: https://jena.apache.org/documentation/query/. [Accessed: 14-Mar-2019]Google ScholarGoogle Scholar

Index Terms

  1. Querying Heterogeneous Property Graph Data Sources based on a Unified Conceptual View

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      ICSIE '20: Proceedings of the 9th International Conference on Software and Information Engineering
      November 2020
      251 pages
      ISBN:9781450377218
      DOI:10.1145/3436829

      Copyright © 2020 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 5 January 2021

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited
    • Article Metrics

      • Downloads (Last 12 months)6
      • Downloads (Last 6 weeks)0

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader