A Review of Accessing Big Data with Significant Ontologies

Jumah Y.J Sleeman; Jehad Abdulhamid Hammad

doi:10.17977/um018v3i22020p67-76

A Review of Accessing Big Data with Significant Ontologies

Jumah Y.J Sleeman, Jehad Abdulhamid Hammad

Abstract

Ontology Based Data Access (OBDA) is a recently proposed approach which is able to provide a conceptual view on relational data sources. It addresses the problem of the direct access to big data through providing end-users with an ontology that goes between users and sources in which the ontology is connected to the data via mappings. We introduced the languages used to represent the ontologies and the mapping assertions technique that derived the query answering from sources. Query answering is divided into two steps: (i) Ontology rewriting, in which the query is rewritten with respect to the ontology into new query; (ii) mapping rewriting the query that obtained from previous step reformulating it over the data sources using mapping assertions. In this survey, we aim to study the earlier works done by other researchers in the fields of ontology, mapping and query answering over data sources.

Full Text:

PDF

References

K. T. Wassif, “A Survey on Using Ontology for Addressing End User Access to Big Data,” Int. J. Comput. Syst., vol. 02, no. 08, pp. 363–372, 2015.

M. Giese et al., “Scalable End-User Access to Big Data,” in Big Data Computing, Chapman and Hall/CRC, 2013, pp.205–244.

F. Di Pinto et al., “Optimizing query rewriting in ontology-based data access,” Proc. 16th Int. Conf. Ext. Database Tech.- EDBT ’13, 2013, p. 561.

M. Bienvenu and R. Rosati, “Query-based comparison of OBDA specifications,” Proc. 28th Int. Work. Descr. Logics (DL 2015), 2015.

H. Wache et al., “Ontology-based Integration of Information - A

Survey of Existing Approaches,” IfCAI-01 Work. Ontol. Inf. Shar., pp. 108–117, 2001.

J. P. Dijcks, Oracle: Big data for the enter- prise. Oracle White Paper, 2012.

S. . Jeong and I. Ghani, “Semantic Computing for Big Data: Approaches, Tools, and Emerging Directions (2011-2014),” KSII Trans. Internet Inf. Syst., vol. 8, no. 6, pp. 2022–2042, Jun. 2014. [8] L. Zuo, “A semantic and agent-based approach to support information retrieval, interoperabil- ity and multi-lateral viewpoints for heterogeneous,” University of London, 2006.

B. C. Grau, E. Kharlamov, and D. Zheleznyakov, “How to Contract Ontologies - Statement of Interest,” pp. 1–5, 2012.

M. Jarrat, “Towards methodological principles for ontology Engineering,” Llniversiteit Brassel, 2005.

D. Lembo, J. Mora, R. Rosati, D. F. Savo, and E. Thorstensen, "Mapping Analysis in Ontology-Based Data Access: Algorithms and Complexity,” Lecture Notes in Computer Science, pp. 217–234, 2015.

V. Jahns, “Principles of data integration by Anhai Doan, Alon Halevy, Zachary Ives,” ACM SIGSOFT Softw. Eng. Notes, vol. 37, no. 5, pp. 43–43, Sep. 2012.

D. Lembo, J. Mora, R. Rosati, D. F. Savo, and E. Thorstensen, "Towards Mapping Analysis in Ontology-Based Data Access,” Conf. Int. Conf. Web Reason. Rule Syst., pp. 108–123, 2014.

N. Antonioli et al., “Ontology-based data access: The experience at the Italian Department of Treasury,” CEUR Workshop Proc., vol.1017, no. January, pp. 9–16, 2013.

D. Lembo, R. Rosati, M. Ruzzi, D. F. Savo, and E. Tocci, "Visualization and management of mappings in ontologybased data access (progress report),” CEUR Workshop Proc., vol. 1193, no. october, pp. 595–607, 2014.

H. Pérez-Urbina, E. Rodríguez-Díaz, M. Grove, G. Konstantinidis, and E. Sirin, “Evaluation of query rewriting approaches for OWL 2,” CEUR Workshop Proc., vol. 943, pp. 32–44, 2012.

M. Giese et al., “Optique: Zooming in on Big Data,” Computer (Long. Beach. Calif)., vol. 48, no. 3, pp. 60–67, 2015.

D. Calvanese et al., “The optique project: Towards OBDA Systems for industry,” CEUR Workshop Proc., vol. 1080,

no. January 2015, 2013.

D. Calvanese et al., “Optique: OBDA Solution for Big Data,” Semant. Web ESWC 2013 Satell. Ereitfs. Springer, pp. 293–295, 2013.

T. Eiter, M. Ortiz, M. Šimkus, T. K. Tran, and G. Xiao, “Query rewriting for Horn-SHIQ plus rules,” Proc. Natl. Conf. Artif. Intell., vol. 1, no. c, pp. 726–733, 2012.

J. P. C. Verhoosel, M. Van Bekkum, and F. K. Van Evert, "Ontology matching for big data applications in the smart dairy farming domain,” CEUR Workshop Proc., vol. 1545, pp. 55–59, 2015.

D. F. Savo et al., “Mastro at work: Experiences on ontology-based data access,” CEUR Workshop Proc., vol. 573, no. June 2014, pp. 20–31, 2010.

D. Calvanese et al., “The MASTRO system for ontology-based data access,” Semant. Web, vol. 2, no. 1, pp. 43–53, 2011.

R. Kontchakov, M. Rodríguez-Muro, and M. Zakharyaschev, "Ontology-Based Data Access with Databases: A Short Course,” Lect. Notes Comp. Sci., 2013, pp. 194–229.

L. E. T. Neto, V. M. P. Vidal, M. A. Casanova, and J. M. Monteiro,“R2RML by Assertion: A Semi-automatic Tool for Generating Customised R2RML Mappings,” Lect. Notes Comp. Sci., 2013, pp. 248–252

DOI: http://dx.doi.org/10.17977/um018v3i22020p67-76