Consolidating drug data on a global scale using Linked Data

• Published in: Journal of biomedical semantics Vol. 8; no. 1; p. 3
• Main Authors: Jovanovik, Milos, Trajanov, Dimitar
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 21.01.2017; BioMed Central
• Subjects: Analysis; Data mining; Databases, Pharmaceutical; Delivery of Health Care; Electronic data processing; Information management; Information Storage and Retrieval - methods; Internet; Medical Informatics - methods; Pharmaceutical industry; Macedonia; Drugs; Drug products; Data consolidation; Linked data; Methodology; Tools; Healthcare; Open data
• DOI: 10.1186/s13326-016-0111-z
• ISSN: 2041-1480

Drug product data is available on the Web in a distributed fashion. The reasons lie within the regulatory domains, which exist on a national level. As a consequence, the drug data available on the Web are independently curated by national institutions from each country, leaving the data in varying languages, with a varying structure, granularity level and format, on different locations on the Web. Therefore, one of the main challenges in the realm of drug data is the consolidation and integration of large amounts of heterogeneous data into a comprehensive dataspace, for the purpose of developing data-driven applications. In recent years, the adoption of the Linked Data principles has enabled data publishers to provide structured data on the Web and contextually interlink them with other public datasets, effectively de-siloing them. Defining methodological guidelines and specialized tools for generating Linked Data in the drug domain, applicable on a global scale, is a crucial step to achieving the necessary levels of data consolidation and alignment needed for the development of a global dataset of drug product data. This dataset would then enable a myriad of new usage scenarios, which can, for instance, provide insight into the global availability of different drug categories in different parts of the world. We developed a methodology and a set of tools which support the process of generating Linked Data in the drug domain. Using them, we generated the LinkedDrugs dataset by seamlessly transforming, consolidating and publishing high-quality, 5-star Linked Drug Data from twenty-three countries, containing over 248,000 drug products, over 99,000,000 RDF triples and over 278,000 links to generic drugs from the LOD Cloud. Using the linked nature of the dataset, we demonstrate its ability to support advanced usage scenarios in the drug domain. The process of generating the LinkedDrugs dataset demonstrates the applicability of the methodological guidelines and the supporting tools in transforming drug product data from various, independent and distributed sources, into a comprehensive Linked Drug Data dataset. The presented user-centric and analytical usage scenarios over the dataset show the advantages of having a de-siloed, consolidated and comprehensive dataspace of drug data available via the existing infrastructure of the Web.