Enabling Web-scale data integration in biomedicine through Linked Open Data

Kamdar, Maulik R. ORCID: https://orcid.org/0000-0002-9898-0515 and Polleres, Axel ORCID: https://orcid.org/0000-0001-5670-1146 and Fernandez Garcia, Javier David ORCID: https://orcid.org/0000-0002-2683-827X and Tudorache, Tania and Musen, Mark A. (2019) Enabling Web-scale data integration in biomedicine through Linked Open Data. npj Digital Medicine, 2 (1). pp. 1-14.

Available under License Creative Commons: Attribution 4.0 International (CC BY 4.0).

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The biomedical data landscape is fragmented with several isolated, heterogeneous data and knowledge sources, which use varying formats, syntaxes, schemas, and entity notations, existing on the Web. Biomedical researchers face severe logistical and technical challenges to query, integrate, analyze, and visualize data from multiple diverse sources in the context of available biomedical knowledge. Semantic Web technologies and Linked Data principles may aid toward Web-scale semantic processing and data integration in biomedicine. The biomedical research community has been one of the earliest adopters of these technologies and principles to publish data and knowledge on the Web as linked graphs and ontologies, hence creating the Life Sciences Linked Open Data (LSLOD) cloud. In this paper, we provide our perspective on some opportunities proffered by the use of LSLOD to integrate biomedical data and knowledge in three domains: (1) pharmacology, (2) cancer research, and (3) infectious diseases. We will discuss some of the major challenges that hinder the wide-spread use and consumption of LSLOD by the biomedical research community. Finally, we provide a few technical solutions and insights that can address these challenges. Eventually, LSLOD can enable the development of scalable, intelligent infrastructures that support artificial intelligence methods for augmenting human intelligence to achieve better clinical outcomes for patients, to enhance the quality of biomedical research, and to improve our understanding of living systems.

Item Type: Article
Keywords: Computational platforms and environments, Data integration, Databases
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft > Polleres
Version of the Document: Published
Depositing User: Gertraud Novotny
Date Deposited: 26 Nov 2019 10:11
Last Modified: 26 Nov 2019 10:11
Related URLs:
FIDES Link: https://bach.wu.ac.at/d/research/results/92881/
URI: https://epub.wu.ac.at/id/eprint/7318


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