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dc.contributor.authorIqbal, Aftab
dc.date.accessioned2014-08-13T12:41:54Z
dc.date.available2014-08-13T12:41:54Z
dc.date.issued2014
dc.identifier.citationMuntazir 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.urihttps://deri.ie/sites/default/files/publications/mmehdi_ideas14_0.pdf
dc.identifier.urihttp://hdl.handle.net/10379/4495
dc.descriptionConference paperen_US
dc.description.abstractA 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.formatapplication/pdfen_US
dc.language.isoenen_US
dc.relation.ispartof18th International Database Engineering & Applications Symposiumen
dc.titleDiscovering Domain-Specific Public SPARQL Endpoints: A Life-Sciences Use-Caseen_US
dc.typeConference Paperen_US
dc.date.updated2014-08-02T23:28:33Z
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funder|~|
dc.internal.rssid6825463
dc.local.contactChaudhry Muhammad Aftab Iqbal, Deri, Ida Business Park, Nui Galway. Email: chaudhrymuhammadaftab.iqbal@nuigalway.ie
dc.local.copyrightcheckedNo
dc.local.versionACCEPTED
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