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Improving discovery in Life Sciences Linked Open Data Cloud

Authors: 

Ali Hasnain, Stefan Decker

Publication Type: 
Edited Conference Meeting Proceeding
Abstract: 
Multiple datasets that add high value to biomedical research have been exposed on the web as part of the Life Sciences Linked Open Data (LSLOD) Cloud. The ability to easily navigate through these datasets is crucial for personalized medicine and the improvement of drug discovery process. However, navigating these multiple datasets is not trivial as most of these are only available as isolated SPARQL endpoints with very little vocabulary reuse. The content that is indexed through these endpoints is scarce, making the indexed dataset opaque for users. We propose an approach to create an active Linked Life Sciences Data Compendium, a set of configurable rules which can be used to discover links between biological entities in the LSLOD cloud. We have catalogued and linked concepts and properties from 137 public SPARQL endpoints. Our Compendium is primarily used to dynamically assemble queries retrieving data from multiple SPARQL endpoints simultaneously.
Conference Name: 
14th International Semantic Web Conference, Bethlehem, Pennsylvania
Digital Object Identifer (DOI): 
N/A
Publication Date: 
12/10/2015
Conference Location: 
United States of America
Research Group: 
Institution: 
NUIG
Open access repository: 
Yes
Publication document: