TY - GEN
T1 - Discovering domain-specific public sparql endpoints
T2 - 18th International Database Engineering and Applications Symposium, IDEAS 2014
AU - Mehdi, Muntazir
AU - Iqbal, Aftab
AU - Hogan, Aidan
AU - Hasnain, Ali
AU - Khan, Yasar
AU - Decker, Stefan
AU - Sahay, Ratnesh
PY - 2014
Y1 - 2014
N2 - A significant portion of the LOD cloud consists of Life Sciences data sets, which together contain billions of clinical facts that interlink to form a "Web of Clinical Data". However, tools for new publishers to find relevant datasets that could potentially be linked to are missing, particularly in specialist domain-specific settings. Based on a set of domainspecific keywords extracted from a local dataset, this paper proposes methods to automatically identify relevant public SPARQL endpoints from a list of candidates.
AB - A significant portion of the LOD cloud consists of Life Sciences data sets, which together contain billions of clinical facts that interlink to form a "Web of Clinical Data". However, tools for new publishers to find relevant datasets that could potentially be linked to are missing, particularly in specialist domain-specific settings. Based on a set of domainspecific keywords extracted from a local dataset, this paper proposes methods to automatically identify relevant public SPARQL endpoints from a list of candidates.
KW - Healthcare and life sciences
KW - Linked Open Data (LOD) Cloud
KW - SPARQL
KW - Web of data
UR - https://www.scopus.com/pages/publications/84906819230
U2 - 10.1145/2628194.2628220
DO - 10.1145/2628194.2628220
M3 - Conference Publication
SN - 9781450326278
T3 - ACM International Conference Proceeding Series
SP - 39
EP - 45
BT - Proceedings of the 18th International Database Engineering and Applications Symposium, IDEAS 2014
PB - Association for Computing Machinery
Y2 - 7 July 2014 through 9 July 2014
ER -