Advertisement

A Survey of Approaches to Representing SPARQL Variables in SQL Queries

  • Miloš Chaloupka
  • Martin Nečaský
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10574)

Abstract

RDF is a universal data model for publishing structured data on the Web. On the other hand, many structured data is stored in relational database systems. To support publishing data in the RDF model, it is essential to close the gap between the relational and RDF worlds. A virtual SPARQL endpoint over relational data is a promising approach to achieve that. To build a virtual SPARQL endpoint, we need to know how to translate SPARQL queries to corresponding SQL queries. There exist several approaches to such transformation. Most of them are focused on the processing of user-defined mapping. The user-defined mapping gives an user the ability to define a mapping of a stored relation data to almost any RDF representation. In this paper we focus on one of the core problems of the transformation: how to represent variables from a given SPARQL query in the corresponding SQL query. We survey variable representations from existing approaches; how the selected representation affects the soundness and performance of the whole transformation approach.

Keywords

RDB2RDF SQL R2RML SPARQL Relational to RDF mapping SPARQL variable representation 

Notes

Acknowledgments

This work was supported by the Charles University in Prague, project GA UK No. #158215 and by the Czech Science Foundation (GAČR), grant number 16-09713S.

References

  1. 1.
    Bizer, C., Schultz, A.: The Berlin SPARQL benchmark. Int. J. Semant. Web Inf. Syst. 5(2), 1–24 (2009). http://dblp.uni-trier.de/db/journals/ijswis/ijswis5.html#BizerS09 CrossRefGoogle Scholar
  2. 2.
    Bizer, C., Schultz, A.: Berlin SPARQL benchmark (BSBM) (2011). http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/. Accessed Mar 2017
  3. 3.
    Brüggemann, S., Bereta, K., Xiao, G., Koubarakis, M.: Ontology-based data access for maritime security. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 741–757. Springer, Cham (2016). doi: 10.1007/978-3-319-34129-3_45 CrossRefGoogle Scholar
  4. 4.
    Calvanese, D., Cogrel, B., Komla-Ebri, S., Kontchakov, R., Lanti, D., Rezk, M., Rodriguez-Muro, M., Xiao, G.: Ontop: answering SPARQL queries over relational databases. Semant. Web 8(3), 471–487 (2017). https://doi.org/10.3233/SW-160217 CrossRefGoogle Scholar
  5. 5.
    Chaloupka, M., Nečaský, M.: Efficient SPARQL to SQL translation with user defined mapping. In: Ngonga Ngomo, A.-C., Křemen, P. (eds.) KESW 2016. CCIS, vol. 649, pp. 215–229. Springer, Cham (2016). doi: 10.1007/978-3-319-45880-9_17 CrossRefGoogle Scholar
  6. 6.
    Chebotko, A., Lu, S., Fotouhi, F.: Semantics preserving SPARQL-to-SQL translation. Data Knowl. Eng. 68(10), 973–1000 (2009)CrossRefGoogle Scholar
  7. 7.
    Chebotko, A., Lu, S., Jamil, H.M., Foutouhi, F.: Semantics preserving SPARQL-to-SQL query translation for optional graph patterns. Wayne State University, Technical report, November 2006Google Scholar
  8. 8.
    Cyganiak, R.: D2RQ. Accessing relational databases as virtual RDF Graphs. http://d2rq.org/. Accessed Mar 2017
  9. 9.
    Das, S., Cyganiak, R., Sundara, S.: R2RML: RDB to RDF mapping language. W3C recommendation, W3C. http://www.w3.org/TR/2012/REC-r2rml-20120927/
  10. 10.
    Harris, S., Seaborne, A.: SPARQL 1.1 query language. W3C recommendation, W3C, March 2013. http://www.w3.org/TR/2013/REC-sparql11-query-20130321/
  11. 11.
    Lanthaler, M., Wood, D., Cyganiak, R.: RDF 1.1 concepts and abstract syntax. W3C recommendation, W3C, September 2012. http://www.w3.org/TR/2014/REC-rdf11-concepts-20140225/
  12. 12.
    Prud’hommeaux, E., Arenas, M., Bertails, A., Sequeda, J.: A direct mapping of relational data to RDF. W3C recommendation, W3C, September 2012. http://www.w3.org/TR/2012/REC-rdb-direct-mapping-20120927/
  13. 13.
    Rodríguez-Muro, M., Rezk, M.: Efficient SPARQL-to-SQL with R2RML mappings. Web Semant. Sci. Serv. Agents. World Wide Web 33(1), 141–169 (2015)CrossRefGoogle Scholar
  14. 14.
    Sequeda, J., Miranker, D.P.: Ultrawrap: SPARQL execution on relational data. Web Semant. Sci. Serv. Agents. World Wide Web 22, 19–39 (2013)CrossRefGoogle Scholar
  15. 15.
    Unbehauen, J., Stadler, C., Auer, S.: Accessing relational data on the web with SparqlMap. In: Takeda, H., Qu, Y., Mizoguchi, R., Kitamura, Y. (eds.) JIST 2012. LNCS, vol. 7774, pp. 65–80. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-37996-3_5 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Mathematics and PhysicsCharles UniversityPraha 1Czech Republic

Personalised recommendations