Consolidating drug data on a global scale using Linked Data

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• 作者：Milos Jovanovik ; Dimitar Trajanov
• 关键词：Methodology ; Drugs ; Drug products ; Healthcare ; Linked data ; Open data ; Data consolidation ; Tools
• 刊名：Journal of Biomedical Semantics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：8
• 期：1
• 全文大小：1247KB
• 刊物主题：Algorithms; Computer Appl. in Life Sciences; Data Mining and Knowledge Discovery; Computational Biology/Bioinformatics; Bioinformatics; Combinatorial Libraries;
• 出版者：BioMed Central
• ISSN：2041-1480
• 卷排序：8

文摘

BackgroundDrug 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.