dc.contributor.author | Iqbal, Aftab | |
dc.date.accessioned | 2014-08-13T12:41:54Z | |
dc.date.available | 2014-08-13T12:41:54Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Muntazir Mehdi and Aftab Iqbal and Aidan Hogan and Ali Hasnain and Yasar Khan and Stefan Decker and Ratnesh Sahay (2014) Discovering Domain-Specific Public SPARQL Endpoints: A Life-Sciences Use-Case 18th International Database Engineering & Applications Symposium Portugal, | en_US |
dc.identifier.uri | https://deri.ie/sites/default/files/publications/mmehdi_ideas14_0.pdf | |
dc.identifier.uri | http://hdl.handle.net/10379/4495 | |
dc.description | Conference paper | en_US |
dc.description.abstract | A significant portion of the LOD cloud consists of Life Sciences data sets. The LOD cloud contains billions of clinical
facts linked together forming an interlinked 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 domain-specific keywords extracted from a local
dataset, this paper proposes methods to automatically identify a list of public SPARQL endpoints whose content relates
to the local dataset. | en_US |
dc.format | application/pdf | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | 18th International Database Engineering & Applications Symposium | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.title | Discovering Domain-Specific Public SPARQL Endpoints: A Life-Sciences Use-Case | en_US |
dc.type | Conference Paper | en_US |
dc.date.updated | 2014-08-02T23:28:33Z | |
dc.description.peer-reviewed | peer-reviewed | |
dc.contributor.funder | |~| | |
dc.internal.rssid | 6825463 | |
dc.local.contact | Chaudhry Muhammad Aftab Iqbal, Deri, Ida Business Park, Nui Galway. Email: chaudhrymuhammadaftab.iqbal@nuigalway.ie | |
dc.local.copyrightchecked | No | |
dc.local.version | ACCEPTED | |
nui.item.downloads | 747 | |