A Linked Data Approach for Querying Heterogeneous Sources

A Linked Data Approach for Querying Heterogeneous Sources

Nikolaos Matskanis, Vasiliki Andronikou, Philippe Massonet, Kostas Mourtzoukos and Joseph Roumier, A Linked Data Approach for Querying Heterogeneous Sources , Assisting Researchers in Finding Answers to Complex Clinical Questions, KEOD 2012, Barcelona Spain, 4-7 October 2012

Date: 4 October 2012

Publication: Scientific papers 

Expertises:

Data Science 

Domaine: Health 

About project: PONTE 

Clinical trials for drug repositioning aim at evaluating the effectiveness and safety of existing drugs for new treatments. This involves managing many interdependent parameters and details in order to clearly identify the research question of the clinical trial and is followed by the challenging step of selection and recruitment of eligible subjects. 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, gene data sources 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 using semantic search technologies in order to produce answers for the clinical researcher’s questions.

View online : A Linked Data Approach for Querying Heterogeneous Sources