Mongo2SPARQL: Automatic and Semantic Query Conversion of MongoDB Query Language to SPARQL
DOI:
https://doi.org/10.14738/tmlai.54.2984Keywords:
Big Data, Mongo2SPARQL, MongoDB, NOSQL, Semantic Web, SPARQL.Abstract
In the last decades, the web has experienced a quantitative explosion of digital data handled by companies or organizations, prompting web users to switch to NoSQL system dedicated to Big Data in order to support large web sites destined for a very big audience due to the scalability and high availability of this system. In the other hand, the semantic web technologies has emerged with their considerable performance in data management by giving the web information a well-defined meaning, and allowing machines to intelligently access to different data sources. However, there is no bridge or an open extension toward these two systems in order to facilitate the interconnection between them; in addition, each NoSQL database has its own query language and does not support the standards of other systems (such as semantic web). All these reasons have motivated us to operate in this topic in order to unify the NoSQL query language and contribute in the interoperability of the both world with a specific focus on MongoDB as a NoSQL document oriented database by proposing the first provably semantic preserving algorithm named Mongo2SPARQL which transform MongoDB query language queries to its equivalent SPARQL ones taking into account key/value pairs having value’s type array and embedded document, generating lists/bags and blank nodes after their transformation.
References
(1) Tudorica, B. G., & Bucur, C. (2011, June). A comparison between several NoSQL databases with comments and notes. In Roedunet International Conference (RoEduNet), 2011 10th (pp. 1-5). IEEE.
(2) Prud’hommeaux, E., & Seaborne, A. (2008). SPARQL query language for RDF. Recommendation, W3C. Retrieved from https://www.w3.org/TR/rdf-sparql-query/. Last visit February 2016.
(3) The MongoDB 3.2 Manual. Retrieved from https://docs.MongoDB.org/manual. Last visit February 2016.
(4) Tomaszuk, D. (2010). Document-oriented triple store based on RDF/JSON.Studies in Logic, Grammar and Rhetoric,(22 (35)).
(5) Curé, O., Lamolle, M., & Duc, C. L. (2013). Ontology based data integration over document and column family oriented NOSQL. arXiv preprint arXiv:1307.2603.
(6) Michel, F., Faron-Zucker, C., & Montagnat, J. (2016). Mapping-based SPARQL access to a MongoDB database (Doctoral dissertation, CNRS).
(7) Rocha, L., Vale, F., Cirilo, E., Barbosa, D., & Mourão, F. (2015). A Framework for Migrating Relational Datasets to NoSQL. Procedia Computer Science, 51, 2593-2602.
(8) Lawrence, R. (2014, March). Integration and virtualization of relational SQL and NoSQL systems including MySQL and MongoDB. In Computational Science and Computational Intelligence (CSCI), 2014 International Conference on (Vol. 1,
pp. 285-290). IEEE.
(9) Khan, S., & Mane, V. (2013). SQL support over MongoDB using metadata.International Journal of Scientific and Research Publications, 3(10), 1-5.
(10) Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific american, 284(5), 28-37.
(11) Beckett, D. (2014, February). Rdf 1.1 xml syntax. W3C recommendation. Retrieved from https://www.w3.org/TR/rdf-syntax-grammar/. Last visit Fabruary 2016.
(12) Bechhofer, S., Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F., Stein, L.A.: OWL Web Ontology Language Reference. W3C Recommendation 10, 2006–10 (2004).
