A Novel Framework for User-Friendly Ontology-Mediated Access to Relational Databases
A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
[1] D. D. Chamberlin, R. F. Boyce, SEQUEL: A structured English query
language, In Proceedings of the 1974 ACM SIGFIDET (now SIGMOD)
workshop on Data description, access and control (SIGFIDET '74), New
York, USA, 1974, pp. 249-264, DOI: 10.1145/800296.811515.
[2] D. Brickley, R. V. Guha, RDF Vocabulary Description Language 1.0:
RDF Schema, W3C Recommendation 10 February 2004,
http://www.w3.org/TR/2004/REC-rdf-schema-20040210/ (accessed
Nov. 2014)
[3] D. L. McGuinness, F. V. Harmelen, OWL Web Ontology Language
Overview, W3C Recommendation 10 February 2004,
http://www.w3.org/TR/owl-features/ (accessed Nov. 2014)
[4] P. Spyns, R. Meersman, M. Jarrar, Data modelling versus ontology
engineering, in SIGMOD Rec., vol. 31, num. 4, December 2002, pp. 12-
17, DOI: 10.1145/637411.637413.
[5] E. Prud'hommeaux, A. Seaborne, SPARQL Query Language for RDF,
W3C Recommendation 15 January 2008, http://www.w3.org/TR/rdfsparql-
query/ (accessed Nov. 2014)
[6] D. Calvanese, G. D. Giacomo, D. Lembo, M. Lenzerini, A. Poggi, M.
Rodriguez-Muro, et al., The MASTRO system for ontology-based data
access, Semant. web, vol. 2, num. 1 , January 2011), pp. 43-53.
[7] A. Soylu, M. Giese, E. Jimenez-Ruiz, E. Kharlamov, D. Zheleznyakov,
I. Horrocks, OptiqueVQS: towards an ontology-based visual query
system for big data, In Proceedings of the Fifth International Conference
on Management of Emergent Digital EcoSystems (MEDES '13). ACM,
New York, NY, USA, 2013, pp. 119-126, DOI:
10.1145/2536146.2536149
[8] M. Rodríguez-Muro, D. Calvanese, Quest, a System for Ontology Based
Data Access, In OWLED 2012, 2012.
[9] D2R Server: Accessing databases with SPARQL and as Linked Data,
available at http://d2rq.org/d2r-server (accessed Nov. 2014)
[10] N. Cullot, R. Ghawi, and K. Yétongnon, DB2OWL: A Tool for
Automatic Database-to-Ontology Mapping, In Proceedings of 15th
Italian Symposium on Advanced Database Systems (SEBD 2007), 2007,
pp. 491–494.
[11] K. Munir, M. Odeh, P. Bloodsworth and R. McClatchey, "Using
Assertion Capabilities of an OWL-Based Ontology for Query
Formulation", 3rd International Conference on Information &
Communication Technologies: from Theory to Applications (ICTTA),
IEEE, Damascus, Syria, 2008.
[12] Flint SPARQL Editor, available at http://cliopatria.swiprolog.
org/flint/index.html (accessed Nov. 2014)
[13] OpenLink Virtuoso SPARQL Query Editor, available at
http://demo.openlinksw.com/sparql/ (accessed Nov. 2014)
[14] Twinkle: A SPARQL Query Tool, available at
http://www.ldodds.com/projects/twinkle/ (accessed Nov. 2014)
[15] R. Cyganiak, C. Bizer, Pubby - A Linked Data Frontend for SPARQL
Endpoints, available at http://wifo5-03.informatik.unimannheim.
de/pubby/ (accessed Nov. 2014)
[16] N. Bikakis, M. Skourla, C. Papastefanatos, "rdf:SynopsViz - A
Framework for Hierarchical Linked Data Visual Exploration and
Analysis", available at http://83.212.97.83:8084/ (accessed Nov. 2014)
[17] F. Haag, S. Lohmann, T. Ertl, SparqlFilterFlow: SPARQL Query
Composition for Everyone, The Semantic Web: ESWC 2014 Satellite
Events, 2014, pp. 362-367, DOI: 10.1007/978-3-319-11955-7_49.
[18] A. Tagaris, V. Andronikou, E. Karanastasis, E. Chondrogiannis, C.
Tsirmpas, T. Varvarigou, D. Koutsouris, PAT: an intelligent authoring
tool for facilitating clinical trial design. Stud Health Technol Inform.,
2014, pp. 205:970-4.
[19] C. Bizer, and A. Seaborne, D2RQ - Treating Non-RDF Databases as
Virtual RDF Graphs, in 'ISWC2004 (posters)', 2004
[20] DB to OWL Tools, available at
http://ponte.grid.ece.ntua.gr:8080/DbToOwl/ (accessed Nov. 2014)
[21] Protégé, available at http://protege.stanford.edu/ (accessed Nov. 2014)
[22] M. Klein, Combining and relating ontologies: an analysis of problems
and solutions, In IJCAI-2001 Workshop on Ontologies and Information
Sharing, Seattle, WA, 2001, pp. 53-62.
[23] E. Chondrogiannis, V. Andronikou, E. Karanastasis, and T. Varvarigou,
An Intelligent Ontology Alignment Tool Dealing with Complicated
Mismatches, Accepted for SWAT4LS Workshop 2014.
[24] EDOAL: Expressive and Declarative Ontology Alignment Language,
available at http://alignapi.gforge.inria.fr/edoal.html (accessed Nov.
2014)
[25] E. Chondrogiannis, V. Andronikou, K. Mourtzoukos, A. Tagaris, and T.
Varvarigou, A novel query rewriting mechanism for semantically
interlinking clinical research with electronic health records, In
Proceedings of the 2nd International Conference on Web Intelligence,
Mining and Semantics (WIMS '12), ACM, New York, USA, 2012, pp.
48:1-48:12, DOI: 10.1145/2254129.2254189.
[26] M. Arenas, J. Perez, Querying semantic web data with SPARQL, In
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART
symposium on Principles of database systems (PODS '11), ACM, New
York, NY, USA, 2011, pp. 305-316, DOI: 10.1145/1989284.1989312.
[27] E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur, and Y. Katz, Pellet: A
practical OWL-DL reasoner. in Web Semantics: Science, Services and
Agents on the World Wide Web, vol. 5, num. 2, 2007, pp. 51-53, DOI:
10.1016/j.websem.2007.03.004.
[28] International Classification of Diseases (ICD), 10th version, available at
http://apps.who.int/classifications/icd10 (accessed Nov. 2014)
[29] G. Bossu, P. Siegel, Saturation, nonmonotonic reasoning and the closedworld
assumption, Artificial Intelligence, vol. 25 num. 1, Jan. 1985, pp.
13-63, Jan. 1985, DOI: 10.1016/0004-3702(85)90040-2.
[30] K. L. Clark, Negation as Failure, Logic and Data Bases, 1978, pp. 293-
322, DOI: 10.1007/978-1-4684-3384-5_11
[31] S. Harris, A. Seaborne, SPARQL 1.1 Query Language, W3C
Recommendation 21 March 2013 (accessed Nov. 2014)
[32] Administrative HL7 sex Code System, available at
https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114
222.4.11.927 (accessed Nov. 2014)
[33] E. Karanastasis, V. Andronikou, E. Chondrogiannis, G. Tsatsaronis, D.
Eisinger, A. Petrova, The OpenScienceLink architecture for novel
services exploiting open access data in the biomedical domain. In:
Proceedings of the 18th Panhellenic Conference on Informatics (PCI
'14), ACM, New York, NY, USA, 2014, pp. 28:1-28:6.
[1] D. D. Chamberlin, R. F. Boyce, SEQUEL: A structured English query
language, In Proceedings of the 1974 ACM SIGFIDET (now SIGMOD)
workshop on Data description, access and control (SIGFIDET '74), New
York, USA, 1974, pp. 249-264, DOI: 10.1145/800296.811515.
[2] D. Brickley, R. V. Guha, RDF Vocabulary Description Language 1.0:
RDF Schema, W3C Recommendation 10 February 2004,
http://www.w3.org/TR/2004/REC-rdf-schema-20040210/ (accessed
Nov. 2014)
[3] D. L. McGuinness, F. V. Harmelen, OWL Web Ontology Language
Overview, W3C Recommendation 10 February 2004,
http://www.w3.org/TR/owl-features/ (accessed Nov. 2014)
[4] P. Spyns, R. Meersman, M. Jarrar, Data modelling versus ontology
engineering, in SIGMOD Rec., vol. 31, num. 4, December 2002, pp. 12-
17, DOI: 10.1145/637411.637413.
[5] E. Prud'hommeaux, A. Seaborne, SPARQL Query Language for RDF,
W3C Recommendation 15 January 2008, http://www.w3.org/TR/rdfsparql-
query/ (accessed Nov. 2014)
[6] D. Calvanese, G. D. Giacomo, D. Lembo, M. Lenzerini, A. Poggi, M.
Rodriguez-Muro, et al., The MASTRO system for ontology-based data
access, Semant. web, vol. 2, num. 1 , January 2011), pp. 43-53.
[7] A. Soylu, M. Giese, E. Jimenez-Ruiz, E. Kharlamov, D. Zheleznyakov,
I. Horrocks, OptiqueVQS: towards an ontology-based visual query
system for big data, In Proceedings of the Fifth International Conference
on Management of Emergent Digital EcoSystems (MEDES '13). ACM,
New York, NY, USA, 2013, pp. 119-126, DOI:
10.1145/2536146.2536149
[8] M. Rodríguez-Muro, D. Calvanese, Quest, a System for Ontology Based
Data Access, In OWLED 2012, 2012.
[9] D2R Server: Accessing databases with SPARQL and as Linked Data,
available at http://d2rq.org/d2r-server (accessed Nov. 2014)
[10] N. Cullot, R. Ghawi, and K. Yétongnon, DB2OWL: A Tool for
Automatic Database-to-Ontology Mapping, In Proceedings of 15th
Italian Symposium on Advanced Database Systems (SEBD 2007), 2007,
pp. 491–494.
[11] K. Munir, M. Odeh, P. Bloodsworth and R. McClatchey, "Using
Assertion Capabilities of an OWL-Based Ontology for Query
Formulation", 3rd International Conference on Information &
Communication Technologies: from Theory to Applications (ICTTA),
IEEE, Damascus, Syria, 2008.
[12] Flint SPARQL Editor, available at http://cliopatria.swiprolog.
org/flint/index.html (accessed Nov. 2014)
[13] OpenLink Virtuoso SPARQL Query Editor, available at
http://demo.openlinksw.com/sparql/ (accessed Nov. 2014)
[14] Twinkle: A SPARQL Query Tool, available at
http://www.ldodds.com/projects/twinkle/ (accessed Nov. 2014)
[15] R. Cyganiak, C. Bizer, Pubby - A Linked Data Frontend for SPARQL
Endpoints, available at http://wifo5-03.informatik.unimannheim.
de/pubby/ (accessed Nov. 2014)
[16] N. Bikakis, M. Skourla, C. Papastefanatos, "rdf:SynopsViz - A
Framework for Hierarchical Linked Data Visual Exploration and
Analysis", available at http://83.212.97.83:8084/ (accessed Nov. 2014)
[17] F. Haag, S. Lohmann, T. Ertl, SparqlFilterFlow: SPARQL Query
Composition for Everyone, The Semantic Web: ESWC 2014 Satellite
Events, 2014, pp. 362-367, DOI: 10.1007/978-3-319-11955-7_49.
[18] A. Tagaris, V. Andronikou, E. Karanastasis, E. Chondrogiannis, C.
Tsirmpas, T. Varvarigou, D. Koutsouris, PAT: an intelligent authoring
tool for facilitating clinical trial design. Stud Health Technol Inform.,
2014, pp. 205:970-4.
[19] C. Bizer, and A. Seaborne, D2RQ - Treating Non-RDF Databases as
Virtual RDF Graphs, in 'ISWC2004 (posters)', 2004
[20] DB to OWL Tools, available at
http://ponte.grid.ece.ntua.gr:8080/DbToOwl/ (accessed Nov. 2014)
[21] Protégé, available at http://protege.stanford.edu/ (accessed Nov. 2014)
[22] M. Klein, Combining and relating ontologies: an analysis of problems
and solutions, In IJCAI-2001 Workshop on Ontologies and Information
Sharing, Seattle, WA, 2001, pp. 53-62.
[23] E. Chondrogiannis, V. Andronikou, E. Karanastasis, and T. Varvarigou,
An Intelligent Ontology Alignment Tool Dealing with Complicated
Mismatches, Accepted for SWAT4LS Workshop 2014.
[24] EDOAL: Expressive and Declarative Ontology Alignment Language,
available at http://alignapi.gforge.inria.fr/edoal.html (accessed Nov.
2014)
[25] E. Chondrogiannis, V. Andronikou, K. Mourtzoukos, A. Tagaris, and T.
Varvarigou, A novel query rewriting mechanism for semantically
interlinking clinical research with electronic health records, In
Proceedings of the 2nd International Conference on Web Intelligence,
Mining and Semantics (WIMS '12), ACM, New York, USA, 2012, pp.
48:1-48:12, DOI: 10.1145/2254129.2254189.
[26] M. Arenas, J. Perez, Querying semantic web data with SPARQL, In
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART
symposium on Principles of database systems (PODS '11), ACM, New
York, NY, USA, 2011, pp. 305-316, DOI: 10.1145/1989284.1989312.
[27] E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur, and Y. Katz, Pellet: A
practical OWL-DL reasoner. in Web Semantics: Science, Services and
Agents on the World Wide Web, vol. 5, num. 2, 2007, pp. 51-53, DOI:
10.1016/j.websem.2007.03.004.
[28] International Classification of Diseases (ICD), 10th version, available at
http://apps.who.int/classifications/icd10 (accessed Nov. 2014)
[29] G. Bossu, P. Siegel, Saturation, nonmonotonic reasoning and the closedworld
assumption, Artificial Intelligence, vol. 25 num. 1, Jan. 1985, pp.
13-63, Jan. 1985, DOI: 10.1016/0004-3702(85)90040-2.
[30] K. L. Clark, Negation as Failure, Logic and Data Bases, 1978, pp. 293-
322, DOI: 10.1007/978-1-4684-3384-5_11
[31] S. Harris, A. Seaborne, SPARQL 1.1 Query Language, W3C
Recommendation 21 March 2013 (accessed Nov. 2014)
[32] Administrative HL7 sex Code System, available at
https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114
222.4.11.927 (accessed Nov. 2014)
[33] E. Karanastasis, V. Andronikou, E. Chondrogiannis, G. Tsatsaronis, D.
Eisinger, A. Petrova, The OpenScienceLink architecture for novel
services exploiting open access data in the biomedical domain. In:
Proceedings of the 18th Panhellenic Conference on Informatics (PCI
'14), ACM, New York, NY, USA, 2014, pp. 28:1-28:6.
@article{"International Journal of Information, Control and Computer Sciences:69224", author = "Efthymios Chondrogiannis and Vassiliki Andronikou and Efstathios Karanastasis and Theodora Varvarigou", title = "A Novel Framework for User-Friendly Ontology-Mediated Access to Relational Databases", abstract = "A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
", keywords = "Ontologies, Relational Databases, SPARQL, Web
Interface.", volume = "9", number = "3", pages = "685-10", }
