Detecting inner-ear anatomical and clinical datasets in the linked open data (LOD) cloud
Mehdi, Muntazir ; Iqbal, Aftab ; Khan, Yasar ; Decker, Stefan ; Sahay, Ratnesh
Mehdi, Muntazir
Iqbal, Aftab
Khan, Yasar
Decker, Stefan
Sahay, Ratnesh
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Publication Date
2015-10-15
Type
Conference Paper
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Mehdi, Muntazir , Iqbal, Aftab , Khan, Yasar , Decker, Stefan , & Sahay, Ratnesh (2015). Detecting Inner-Ear Anatomical and Clinical Datasets in the Linked Open Data (LOD) Cloud. Paper presented at the 14th International Semantic Web Conference (ISWC), Pennsylvania, USA, 15 October.
Abstract
Linked Open Data (LOD) Cloud is a mesh of open datasets coming from different domains. Among these datasets, a notable amount of datasets belong to the life sciences domain linked together forming an interlinked “Life Sciences Linked Open Data (LSLOD) Cloud”. One of the key challenges for data publishers is to identify and establish links between newly generated domain specific datasets and LSLOD Cloud. While a number of publishing tools exist for creating links from new to existing datasets, tools to detect domain-specific relevant datasets for linking purposes are missing. In this paper, we propose an extended technique for automatically identifying relevant datasets in LSLOD Cloud for inner-ear anatomical and clinical terminologies. We validate the proposed technique with experiments over the publicly accessible LSLOD Cloud using realworld terminologies and datasets provided by clinical organizations.
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CEUR-WS.org
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Attribution-NonCommercial-NoDerivs 3.0 Ireland