End-User Access to Big Data Using Ontologies

Course at the
1st International Winter School on Big Data (BigDat 2015)
Terragona, Spain, 26-30 January 2015

Diego Calvanese

Research Centre for Knowledge and Data (KRDB)
Free University of Bozen-Bolzano

Slides of the course

  1. Overview of the course
  2. Part 1: Modeling information through ontologies [2 hours]
  3. Part 2: Querying data and knowledge [1 hour]
  4. Part 3: Ontology based data access [3 hours]


Ontologies allow one to describe complex domains at a high level of abstraction, providing end-users with an integrated coherent view over data sources that maintain the information of interest. In addition, ontologies provide mechanisms for performing automated inference over data taking into account domain knowledge, thus supporting a variety of data management tasks. Ontology-based Data Access (OBDA) is a recent paradigm concerned with providing access to data sources through a mediating ontology, which has gained increased attention both from the knowledge representation and from the database communities. OBDA poses significant challenges in the context of accessing large volumes of data with a complex structure and high dinamicity. It thus requires not only carefully tailored languages for expressing the ontology and the mapping to the data, but also suitably optimized algorithms for efficiently processing queries over the ontology by directly accessing the underlying data sources.

In this course we start by introducing the foundations of OBDA relying on the OWL2 QL fragment of the W3C standard Web Ontology Language OWL2. Such language is based on the DL-Lite family of lightweight ontology languages. We discuss the use of ontologies for accessing structured data sources, and turn then to the problems of query answering and inference over large amounts of data stored in such sources. We present novel theoretical and practical results for OBDA that are currently being developed in the context of the FP7 large scale integrating project Optique. These results make it possible to scale the OBDA approach so as to cope with the challenges that arise in complex real world scenarios coming from different domains.


  1. Modeling information through ontologies
  2. Querying data and knowledge
  3. Ontology based data access


[1] Ontologies and databases: The DL-Lite approach. D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini, A. Poggi, M. Rodriguez-Muro, and R. Rosati. In Semantic Technologies for Information Systems - 5th Int. Reasoning Web Summer School (RW 2009), volume 5689 of LNCS, pages 255-356. Springer, 2009. Also available here.

[2] Ontology-based Data Access: Ontop of Databases. M. Rodriguez-Muro, R. Kontchakov, M. Zakharyaschev. In Proc. of the 12th Int. Semantic Web Conference (ISWC 2013). Vol. 8218, pages 558-573. Springer, 2013.

[3] High performance query answering over DL-Lite ontologies. M. Rodriguez-Muro and Diego Calvanese. In Proc. of the 13th international Conference on the Principles of Knowledge Representation and Reasoning (KR 2012), pages 308-318. AAAI Press, 2012.

[3] The Description Logic Handbook: Theory, Implementation and Applications (2nd edition). Edited by F. Baader, D. Calvanese, D. McGuinness, D. Nardi, P.F. Patel-Schneider. Cambridge University Press, 2007.

Presentation style: lectures with slides

Prerequisite knowledge: Basics about relational databases, first-order logic, and data modeling. A background in logics for knowledge representation, description logics, and complexity theory, might be useful, but is not required to follow the course.

Course duration: three lectures of 2 hours each

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Last modified: Thursday, 30-Jan-2020 22:34:36 CET