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Authors: Nikolaos Matskanis 1 ; Vassiliki Andronikou 2 ; Philippe Massonet 3 ; Kostas Mourtzoukos 2 and Joseph Roumier 4

Affiliations: 1 1Centre d’ Excellence en Technologies de l’ Information et de la Communication (CETIC), Belgium ; 2 National Technical University of Athens, Greece ; 3 Centre d’ Excellence en Technologies de l’ Information et de la Communication (CETIC), Belgium ; 4 Centre d’ Excellence en Technologies de l’ Information et de la Communication (CETIC) and, Belgium

Keyword(s): Semantic Search, Heterogeneous Data Sources Querying, Semantic Aggregation of Data.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Collaboration and e-Services ; Data Engineering ; e-Business ; Enterprise Information Systems ; Information Integration ; Integration/Interoperability ; Knowledge Acquisition ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Symbolic Systems

Abstract: Clinical trials for drug repositioning aim at evaluating the effectiveness and safety of existing drugs as new treatments. This involves managing and semantically correlating many interdependent parameters and details in order to clearly identify the research question of the clinical trial. This work, which is carried out within the PONTE (Efficient Patient Recruitment for Innovative Clinical Trials of Existing Drugs) project, aims to improve the trial design process, by not only offering access to a variety of relevant data sources – including, but not limited to, drug profiles, diseases and their mechanisms, genes and past trial results – but also providing the ability to navigate through these sources, perform queries on them and intelligently fuse the available information through semantic reasoning. This article describes our intention to consume and aggregate information from Linked Data sources in order to produce answers for the clinical researcher’s questions.

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Paper citation in several formats:
Matskanis, N.; Andronikou, V.; Massonet, P.; Mourtzoukos, K. and Roumier, J. (2012). A Linked Data Approach for Querying Heterogeneous Sources - Assisting Researchers in Finding Answers to Complex Clinical Questions. In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2012) - KEOD; ISBN 978-989-8565-30-3; ISSN 2184-3228, SciTePress, pages 411-414. DOI: 10.5220/0004173004110414

@conference{keod12,
author={Nikolaos Matskanis. and Vassiliki Andronikou. and Philippe Massonet. and Kostas Mourtzoukos. and Joseph Roumier.},
title={A Linked Data Approach for Querying Heterogeneous Sources - Assisting Researchers in Finding Answers to Complex Clinical Questions},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2012) - KEOD},
year={2012},
pages={411-414},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004173004110414},
isbn={978-989-8565-30-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2012) - KEOD
TI - A Linked Data Approach for Querying Heterogeneous Sources - Assisting Researchers in Finding Answers to Complex Clinical Questions
SN - 978-989-8565-30-3
IS - 2184-3228
AU - Matskanis, N.
AU - Andronikou, V.
AU - Massonet, P.
AU - Mourtzoukos, K.
AU - Roumier, J.
PY - 2012
SP - 411
EP - 414
DO - 10.5220/0004173004110414
PB - SciTePress