Ontology-Based Approaches to Big Data Analytics

  • Agnieszka Konys
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 534)


The access to relevant information is one of the determining factors which directly influences on decision-making processes. Huge amounts of data have been accumulated by entities from large variety of sources in many different formats. Due to large amounts of information and continuous processes of generation of new parts, it is necessary to ensure the most effective way of information or data extraction and analysis. The Web of Data provides great opportunities for ontology-based services. The combination of ontology-based approaches and Big Data may help in solving some problems related to extraction of meaningful information from various sources. This paper presents the selected ontology-based approaches to Big Data analytics as well as a proposal of a procedure for ontology-based knowledge discovery.


Ontology Data access Data analysis Big Data Data extraction 


  1. 1.
    Rodríguez-Muro, M., Kontchakov, R., Zakharyaschev, M.: Ontology-based data access: ontop of databases. In: Alani, H., et al. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 558–573. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-41335-3_35 Google Scholar
  2. 2.
    Savo, D.F., Lembo, D., Lenzerini, M., Poggi, A., Rodriguez-Muro, M., Romagnoli, V., Ruzzi, M., Stella, G.: MASTRO at work: experiences on ontology-based data access. In: Proceedings of the 23rd International Workshop on Description Logics (DL2010), CEUR WS 573, Waterloo, Canada (2010)Google Scholar
  3. 3.
    Lembo, D., Mora, J., Rosati, R., Savo, D.F., Thorstensen, E.: Mapping analysis in ontology-based data access: algorithms and complexity. In: Arenas, M., et al. (eds.) ISWC 2015, Part I. LNCS, vol. 9366, pp. 217–234. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-25007-6_13 CrossRefGoogle Scholar
  4. 4.
    Heymans, S., et al.: Ontology reasoning with large data repositories. In: Hepp, M., et al. (eds.) Ontology Management. Computing for Human Experience, vol. 7, pp. 89–128. Springer, US (2008)CrossRefGoogle Scholar
  5. 5.
    Konys, A.: Knowledge-based approach to question answering system selection. In: Núñez, M., Nguyen, N.T., Camacho, D., Trawiński, B. (eds.) ICCCI 2015, Part I. LNCS (LNAI), vol. 9329, pp. 361–370. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-24069-5_34 CrossRefGoogle Scholar
  6. 6.
    Ajani, S.: An ontology and semantic metadata based semantic search technique for census domain in a big data context. Int. J. Eng. Res. Technol. 3(2), 1–5 (2014)Google Scholar
  7. 7.
    Kitchin, R., McArdle, G.: What makes big data, big data? Exploring the ontological characteristics of 26 datasets. Big Data Soc. 3, 1–10 (2016)Google Scholar
  8. 8.
    Murthy, P., Bharadwaj, A., Subrahmanyam, P.A., et al.: Big Data Taxonomy. Big Data Working Group, Cloud Security Alliance (2014)Google Scholar
  9. 9.
    Konys, A.: A tool supporting mining based approach selection to automatic ontology construction. IADIS J. Comput. Sci. Inf. Syst., 3–10 (2015)Google Scholar
  10. 10.
    Hellmann, S., Auer, S.: Towards web-scale collaborative knowledge extraction. In: Gurevych, I., Kim, J. (eds.) The People’s Web Meets NLP, Theory and Applications of Natural Language Processing, pp. 287–313. Springer, Heidelberg (2013)Google Scholar
  11. 11.
    Unbehauen, J., Hellmann, S., Auer, S., Stadler, C.: Knowledge extraction from structured sources. In: Ceri, S., Brambilla, M. (eds.) Search Computing. LNCS, vol. 7538, pp. 34–52. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-34213-4_3 CrossRefGoogle Scholar
  12. 12.
    Gruninger, M., Obst, L.: Semantic web and big data meets applied ontology. Appl. Ontol. 9, 155–170 (2014)Google Scholar
  13. 13.
    Kuiler, E.W.: From big data to knowledge: an ontological approach to big data analytics. Rev. Policy Res. 31(4), 311–318 (2014)CrossRefGoogle Scholar
  14. 14.
    Kitchin, R.: The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. Sage, London (2014)CrossRefGoogle Scholar
  15. 15.
    Calvanese, D., et al.: The mastro system for ontology-based data access. Semant. Web J. 2(1), 43–53 (2011)Google Scholar
  16. 16.
    Kozaki K.: Ontology engineering for big data. In: Ontology and Semantic Web for Big Data (ONSD2013) Workshop in the 2013 International Computer Science and Engineering Conference (ICSEC2013), Bangkok, Thailand (2013)Google Scholar
  17. 17.
    Gruber, T.: Toward principles for the design of ontologies used for knowledge sharing. Int. J. Hum Comput Stud. 43(5–6), 907–928 (1995)CrossRefGoogle Scholar
  18. 18.
    Tsai, C.W., et al.: Big data analytics: a survey. J. Big Data 2, 21 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Computer Science and Information TechnologyWest Pomeranian University of Technology in SzczecinSzczecinPoland

Personalised recommendations