This article is part of the supplement: Semantic Web Applications and Tools for Life Sciences, 2008

Open Access Research

KA-SB: from data integration to large scale reasoning

María del Mar Roldán-García, Ismael Navas-Delgado, Amine Kerzazi, Othmane Chniber, Joaquín Molina-Castro and José F Aldana-Montes*

  • * Corresponding author: José F Aldana-Montes

  • † Equal contributors

Author Affiliations

Computer Languages and Computing Science Department, Higher Technical School of Computer Science Engineering, University of Málaga, Málaga, 29071, Spain

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BMC Bioinformatics 2009, 10(Suppl 10):S5  doi:10.1186/1471-2105-10-S10-S5

Published: 1 October 2009



The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data.


KA-SB is a querying and analysis system for final users based on combining a data integration solution with a reasoner. Thus, the tool has been created with a process divided into two steps: 1) KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information from heterogeneous and distributed databases; 2) the integrated information is crystallized in a (persistent and high performance) reasoner (DBOWL). This information could be further analyzed later (by means of querying and reasoning).


In this paper we present a novel system that combines the use of a mediation system with the reasoning capabilities of a large scale reasoner to provide a way of finding new knowledge and of analyzing the integrated information from different databases, which is retrieved as a set of ontology instances. This tool uses a graphical query interface to build user queries easily, which shows a graphical representation of the ontology and allows users o build queries by clicking on the ontology concepts.


These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a process for creating persistent and scalable knowledgebases from sets of OWL instances obtained by integrating heterogeneous data sources with KOMF. This process has been applied to develop a demo tool webcite, which uses the BioPax Level 3 ontology as the integration schema, and integrates UNIPROT, KEGG, CHEBI, BRENDA and SABIORK databases.