research-article

Ontop: : Answering SPARQL queries over relational databases

Editor: Óscar Corcho Authors: Diego Calvanese, Benjamin Cogrel, Sarah Komla-Ebri, Roman Kontchakov, Davide Lanti, Martin Rezk, Mariano Rodriguez-Muro, Guohui XiaoAuthors Info & Claims

Semantic Web, Volume 8, Issue 3

Pages 471 - 487

https://doi.org/10.3233/SW-160217

Published: 01 January 2017 Publication History

Abstract

We present Ontop, an open-source Ontology-Based Data Access (OBDA) system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. Key features of Ontop are its solid theoretical foundations, a virtual approach to OBDA, which avoids materializing triples and is implemented through the query rewriting technique, extensive optimizations exploiting all elements of the OBDA architecture, its compliance to all relevant W3C recommendations (including SPARQL queries, R2RML mappings, and OWL 2 QL and RDFS ontologies), and its support for all major relational databases.

References

[1]

A. Acciarri, D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini, M. Palmieri and R. Rosati, QuOnto: Querying ontologies, in: Proc. of the 20th Nat. Conf. on Artificial Intelligence (AAAI), AAAI Press, 2005, pp. 1670–1671.

[2]

M. Acosta, M.-E. Vidal, T. Lampo, J. Castillo and E. Ruckhaus, ANAPSID: An adaptive query processing engine for SPARQL endpoints, in: Proc. of the 10th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 7031, Springer, 2011, pp. 18–34.

[3]

A. Artale, D. Calvanese, R. Kontchakov and M. Zakharyaschev, The DL-Lite family and relations, J. of Artificial Intelligence Research 36 (2009), 1–69.

[4]

B. Bishop and S. Bojanov, Implementing OWL 2 RL and OWL 2 QL rule-sets for OWLIM, in: Proc. of the 8th Int. Workshop on OWL: Experiences and Directions (OWLED), CEUR Electronic Workshop Proceedings, Vol. 796, CEUR-WS.org, 2011.

[5]

B. Bishop, A. Kiryakov, D. Ognyanoff, I. Peikov, Z. Tashev and R. Velkov, OWLIM: A family of scalable semantic repositories, Semantic Web J. 2(1) (2011), 33–42.

Digital Library

[6]

E. Botoeva, D. Calvanese, V. Santarelli, D.F. Savo, A. Solimando and G. Xiao, Beyond OWL 2 QL in OBDA: Rewritings and approximations, in: Proc. of the 30th AAAI Conf. on Artificial Intelligence (AAAI), AAAI Press, 2016.

[7]

B. Bouchou and C. Niang, Semantic mediator querying, in: Proc. of the 18th Int. Database Engineering & Applications Symposium (IDEAS), ACM Press, 2014, pp. 29–38.

Digital Library

[8]

D. Brickley and R.V. Guha, RDF vocabulary description language 1.0: RDF Schema, W3C Recommendation, World Wide Web Consortium, February 2004, Available at http://www.w3.org/TR/rdf-schema/.

[9]

J. Broekstra, A. Kampman and F. van Harmelen, Sesame: A generic architecture for storing and querying RDF and RDF schema, in: Proc. of the 1st Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 2342, Springer, 2002, pp. 54–68.

[10]

D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini, A. Poggi, M. Rodriguez-Muro, R. Rosati, M. Ruzzi and D.F. Savo, The Mastro system for ontology-based data access, Semantic Web J. 2(1) (2011), 43–53.

[11]

D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini and R. Rosati, Tractable reasoning and efficient query answering in description logics: The DL-Lite family, J. of Automated Reasoning 39(3) (2007), 385–429.

Digital Library

[12]

D. Calvanese, M. Giese, D. Hovland and M. Rezk, Ontology-based integration of cross-linked datasets, in: Proc. of the 14th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 9366, Springer, 2015, pp. 199–216.

Digital Library

[13]

D. Calvanese, C.M. Keet, W. Nutt, M. Rodriguez-Muro and G. Stefanoni, Web-based graphical querying of databases through an ontology: The Wonder system, in: Proc. of the 25th ACM Symposium on Applied Computing (SAC), ACM Press, 2010, pp. 1388–1395.

Digital Library

[14]

D. Calvanese, A. Mosca, J. Remesal, M. Rezk and G. Rull, A ‘historical case’ of ontology-based data access, in: Proc. of Digital Heritage 2015 (DH 2015), IEEE Computer Society Press, 2015.

[15]

T. Catarci, P. Dongilli, T. Di Mascio, E. Franconi, G. Santucci and S. Tessaris, An ontology based visual tool for query formulation support, in: Proc. of the 16th Eur. Conf. on Artificial Intelligence (ECAI), IOS Press, 2004, pp. 308–312.

[16]

U.S. Chakravarthy, J. Grant and J. Minker, Logic-based approach to semantic query optimization, ACM Trans. on Database Systems 15(2) (1990), 162–207.

Digital Library

[17]

S. Das, S. Sundara and R. Cyganiak, R2RML: RDB to RDF mapping language, W3C Recommendation, World Wide Web Consortium, September 2012, Available at http://www.w3.org/TR/r2rml/.

[18]

A. Doan, P. Domingos and A. Halevy, Learning to match the schemas of data sources: A multistrategy approach, Machine Learning 50(3) (2003), 279–301.

Digital Library

[19]

A. Doan, J. Madhavan, R. Dhamankar, P. Domingos and A. Halevy, Learning to match ontologies on the semantic web, The VLDB Journal 12(4) (2003), 303–319.

Digital Library

[20]

R. Fagin, L.M. Haas, M.A. Hernández, R.J. Miller, L. Popa and Y. Velegrakis, Clio: Schema mapping creation and data exchange, in: Conceptual Modeling: Foundations and Applications – Essays in Honor of John Mylopoulos, Lecture Notes in Computer Science, Vol. 5600, 2009, pp. 198–236.

Digital Library

[21]

L. Frontino de Medeiros, F. Priyatna and O. Corcho, MIRROR: Automatic R2RML mapping generation from relational databases, in: Proc. of the 15th Int. Conf. on Web Engineering (ICWE), Lecture Notes in Computer Science, Vol. 9114, Springer, 2015, pp. 326–343.

Digital Library

[22]

M. Giese, A. Soylu, G. Vega-Gorgojo, A. Waaler, P. Haase, E. Jiménez-Ruiz, D. Lanti, M. Rezk, G. Xiao, Ö.L. Özçep and R. Rosati, Optique – zooming in on big data access, IEEE Computer 48(3) (2015), 60–67.

Digital Library

[23]

G. Gottlob, S. Kikot, R. Kontchakov, V.V. Podolskii, T. Schwentick and M. Zakharyaschev, The price of query rewriting in ontology-based data access, Artificial Intelligence 213 (2014), 42–59.

Digital Library

[24]

F. Haag, S. Lohmann, S. Siek and T. Ertl, QueryVOWL: A visual query notation for linked data, in: Proc. of the 3rd Int. Workshop on Human Semantic Web Interaction (HSWI), ESWC 2015 Satellite Events, Lecture Notes in Computer Science, Vol. 9341, Springer, 2015, pp. 387–402.

Digital Library

[25]

M. Horridge and S. Bechhofer, The OWL API: A Java API for OWL ontologies, Semantic Web J. 2(1) (2011), 11–21.

Digital Library

[26]

E. Jiménez-Ruiz, B. Cuenca Grau, Y. Zhou and I. Horrocks, Large-scale interactive ontology matching: Algorithms and implementation, in: Proc. of the 20th European Conf. on Artificial Intelligence (ECAI), Vol. 242, IOS Press, 2012, pp. 444–449.

[27]

E. Jimenez-Ruiz, E. Kharlamov, D. Zheleznyakov, I. Horrocks, C. Pinkel and M.G. Skjæveland, E. Thorstensen and J. Mora, BootOX: Practical mapping of RDBs to OWL 2, in: Proc. of the 14th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 9367, Springer, 2015, pp. 113–132.

Digital Library

[28]

C.M. Keet, R. Alberts, A. Gerber and G. Chimamiwa, Enhancing web portals with ontology-based data access: The case study of South Africa’s Accessibility Portal for people with disabilities, in: Proc. of the 5th Int. Workshop on OWL: Experiences and Directions (OWLED), CEUR Electronic Workshop Proceedings, Vol. 432, CEUR-WS.org, 2008.

[29]

E. Kharlamov, D. Hovland, E. Jimenez-Ruiz, D. Lanti, H. Lie, C. Pinkel, M. Rezk, M.G. Skjæveland, E. Thorstensen, G. Xiao, D. Zheleznyakov and I. Horrocks, Ontology based access to exploration data at Statoil, in: Proc. of the 14th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 9367, Springer, 2015, pp. 93–112.

Digital Library

[30]

E. Kharlamov, N. Solomakhina, Ö.L. Özçep, D. Zheleznyakov, T. Hubauer, S. Lamparter, M. Roshchin, A. Soylu and S. Watson, How semantic technologies can enhance data access at Siemens Energy, in: Proc. of the 13th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 8796, Springer, 2014, pp. 601–619.

Digital Library

[31]

S. Kikot, R. Kontchakov and M. Zakharyaschev, Conjunctive query answering with OWL 2 QL, in: Proc. of the 13th Int. Conf. on Principles of Knowledge Representation and Reasoning (KR), AAAI Press, 2012, pp. 275–285.

[32]

J.J. King, QUIST: A system for semantic query optimization in relational databases, in: Proc. of the 7th Int. Conf. on Very Large Data Bases (VLDB), IEEE Computer Society, 1981, pp. 510–517.

[33]

C.A. Knoblock, P.A. Szekely, J.L. Ambite, A. Goel, S. Gupta, K. Lerman, M. Muslea, M. Taheriyan and P. Mallick, Semi-automatically mapping structured sources into the Semantic Web, in: Proc. of the 9th Extended Semantic Web Conf. (ESWC), Lecture Notes in Computer Science, Vol. 7295, Springer, 2012, pp. 375–390.

Digital Library

[34]

R. Kontchakov, M. Rezk, M. Rodriguez-Muro, G. Xiao and M. Zakharyaschev, Answering SPARQL queries over databases under OWL 2 QL entailment regime, in: Proc. of the 13th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 8796, Springer, 2014, pp. 552–567.

Digital Library

[35]

D. Lanti, M. Rezk, G. Xiao and D. Calvanese, The NPD benchmark: Reality check for OBDA systems, in: Proc. of the 18th Int. Conf. on Extending Database Technology (EDBT), OpenProceedings.org, 2015, pp. 617–628.

[36]

D. Lembo, V. Santarelli and D.F. Savo, Graph-based ontology classification in OWL 2 QL, in: Proc. of the 10th Extended Semantic Web Conf. (ESWC), Lecture Notes in Computer Science, Vol. 7882, Springer, 2013, pp. 320–334.

[37]

V. Lopez, M. Stephenson, S. Kotoulas and P. Tommasi, Data access linking and integration with DALI: Building a safety net for an ocean of city data, in: Proc. of the 14th Int. Semantic Web Conf. (ISWC), Part II, Lecture Notes in Computer Science, Vol. 9367, Springer, 2015, pp. 186–202.

Digital Library

[38]

B. Motik, B. Cuenca Grau, I. Horrocks, Z. Wu, A. Fokoue and C. Lutz, OWL 2 Web Ontology Language profiles (second edition), W3C Recommendation, World Wide Web Consortium, December 2012, Available at http://www.w3.org/TR/owl2-profiles/.

[39]

B. Motik, Y. Nenov, R. Piro, I. Horrocks and D. Olteanu, Parallel materialisation of Datalog programs in centralised, main-memory RDF systems, in: Proc. of the 28th AAAI Conf. on Artificial Intelligence (AAAI), AAAI Press, 2014, pp. 129–137.

[40]

J.S. Nye Jr., The benefits of soft power, Technical report, Harvard University – Business School, 2004, Available at http://hbswk.hbs.edu/archive/4290.html.

[41]

Ö.L. Özçep and R. Möller, Ontology based data access on temporal and streaming data, in: Reasoning Web, Reasoning on the Web in the Big Data Era – 10th Int. Summer School Tutorial Lectures (RW), Lecture Notes in Computer Science, Vol. 8714, Springer, 2014, pp. 279–312.

[42]

A. Poggi, D. Lembo, D. Calvanese, G. De Giacomo, M. Lenzerini and R. Rosati, Linking data to ontologies, J. on Data Semantics X (2008), 133–173.

[43]

A. Poggi, M. Rodríguez-Muro and M. Ruzzi, Ontology-based database access with DIG-Mastro and the OBDA Plugin for Protégé, in: Proc. of the 4th Int. Workshop on OWL: Experiences and Directions (OWLED DC), K. Clark and P.F. Patel-Schneider, eds, 2008.

[44]

F. Priyatna, O. Corcho and J. Sequeda, Formalisation and experiences of R2RML-based SPARQL to SQL query translation using Morph, in: Proc. of the 23rd Int. World Wide Web Conf. (WWW), ACM, 2014, pp. 479–490.

Digital Library

[45]

S. Pugacs, Efficient query answering with semantic indexes, BSc thesis, KRDB Research Centre for Knowledge and Data, Free University of Bozen-Bolzano, 2011.

[46]

A. Rahimi, S. Liaw, J. Taggart, P. Ray and H. Yu, Validating an ontology-based algorithm to identify patients with type 2 diabetes mellitus in electronic health records, Int. J. of Medical Informatics 83(10) (2014), 768–778.

[47]

M. Rodriguez-Muro, Tools and techniques for ontology based data access in lightweight description logics, PhD thesis, KRDB Research Centre for Knowledge and Data, Free University of Bozen-Bolzano, 2010.

[48]

M. Rodriguez-Muro and D. Calvanese, Towards an open framework for ontology based data access with Protégé and DIG 1.1, in: Proc. of the 5th Int. Workshop on OWL: Experiences and Directions (OWLED), CEUR Electronic Workshop Proceedings, Vol. 432, 2008.

[49]

M. Rodríguez-Muro and D. Calvanese, Dependencies: Making ontology based data access work in practice, in: Proc. of the 5th Alberto Mendelzon Int. Workshop on Foundations of Data Management (AMW), CEUR Electronic Workshop Proceedings, Vol. 749, 2011.

[50]

M. Rodriguez-Muro and D. Calvanese, High performance query answering over DL-Lite ontologies, in: Proc. of the 13th Int. Conf. on Principles of Knowledge Representation and Reasoning (KR), AAAI Press, 2012, pp. 308–318.

[51]

M. Rodriguez-Muro, R. Kontchakov and M. Zakharyaschev, Ontology-based data access: Ontop of databases, in: Proc. of the 12th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 8218, Springer, 2013, pp. 558–573.

Digital Library

[52]

M. Rodriguez-Muro, L. Lubyte and D. Calvanese, Realizing ontology based data access: A plug-in for Protégé, in: Proc. of the ICDE Workshop on Information Integration Methods, Architectures, and Systems (IIMAS), IEEE Computer Society Press, 2008, pp. 286–289.

[53]

M. Rodriguez-Muro and M. Rezk, Efficient SPARQL-to-SQL with R2RML mappings, J. of Web Semantics 33 (2015), 141–169.

[54]

M. Rodriguez-Muro, M. Rezk, J. Hardi, M. Slusnys, T. Bagosi and D. Calvanese, Evaluating SPARQL-to-SQL translation in Ontop, in: Proc. of the 2nd Int. Workshop on OWL Reasoner Evaluation (ORE), CEUR Electronic Workshop Proceedings, Vol. 1015, 2013, pp. 94–100.

[55]

A. Schwarte, P. Haase, K. Hose, R. Schenkel and M. Schmidt, FedX: A federation layer for distributed query processing on linked open data, in: Proc. of the 8th Extended Semantic Web Conf. (ESWC), Lecture Notes in Computer Science, Vol. 6644, Springer, 2011, pp. 481–486.

[56]

J.F. Sequeda, M. Arenas and D.P. Miranker, OBDA: Query rewriting or materialization? In practice, both! in: Proc. of the 13th Int. Semantic Web Conf. (ISWC), Lecture Notes in Computer Science, Vol. 8796, Springer, 2014, pp. 535–551.

Digital Library

[57]

M.G. Skjæveland and E.H. Lian, Benefits of publishing the Norwegian Petroleum Directorate’s FactPages as Linked Open Data, in: Proc. of Norsk Informatikkonferanse (NIK 2013), Tapir, 2013.

[58]

A. Soylu, E. Kharlamov, D. Zheleznyakov, E. Jimenez-Ruiz, M. Giese and I. Horrocks, Ontology-based visual query formulation: An industry experience, in: Proc. of the 11th Int. Symposium on Visual Computing (ISVC), Lecture Notes in Computer Science, Vol. 9474, Springer, 2015, pp. 842–854.

[59]

M.M. Tsangaris, G. Kakaletris, H. Kllapi, G. Papanikos, F. Pentaris, P. Polydoras, E. Sitaridi, V. Stoumpos and Y.E. Ioannidis, Dataflow processing and optimization on grid and cloud infrastructures, Bull. of the IEEE Computer Society Technical Committee on Data Engineering 32(1) (2009), 67–74.

[60]

D. Tunkelang, Faceted Search, Synthesis Lectures on Information Concepts, Retrieval, and Services, Morgan & Claypool Publishers, 2009.

[61]

G. Xiao, M. Rezk, M. Rodriguez-Muro and D. Calvanese, Rules and ontology based data access, in: Proc. of the 8th Int. Conf. on Web Reasoning and Rule Systems (RR), Lecture Notes in Computer Science, Vol. 8741, Springer, 2014, pp. 157–172.

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Index Terms

Ontop: Answering SPARQL queries over relational databases
1. Information systems
  1. Data management systems
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

Index terms have been assigned to the content through auto-classification.

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cover image Semantic Web

Semantic Web Volume 8, Issue 3

2017

153 pages

ISSN:1570-0844

EISSN:2210-4968

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Netherlands

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Published: 01 January 2017

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https://dl.acm.org/doi/10.1145/3653317
Ajarroud OZellou AIdri A(2024)A new ontology-based similarity approach for measuring caching coverages provided by mediation systemsKnowledge and Information Systems10.1007/s10115-023-01974-866:2(959-987)Online publication date: 1-Feb-2024
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