End-User Access to Big Data Using
Course at the
1st International Winter School on Big Data
Terragona, Spain, 26-30 January, 2015.
Research Centre for Knowledge and Data (KRDB)
Free University of Bozen-Bolzano
Slides of the course
- Overview of the course
- Part 1: Modeling information
through ontologies [2 hours]
- Part 2: Querying data and
knowledge [1 hour]
- 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
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.
- Modeling information through ontologies
- Data and information modeling
- Ontology languages
- Logics-based approach to conceptual modeling
- Querying data and knowledge
- Querying databases and ontologies
- Query answering in Description Logics
- Ontology based data access
- The DL-lite family of tractable Description Logics
- Reasoning in DL-Lite
- Linking ontologies to relational data
- Conclusions and further work
 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
 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.
 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.
 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.
lectures with slides
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
home page of Diego Calvanese
Monday, 27-Feb-2017 2:57:08 CET