Consolidating drug data on a global scale using Linked Data

Abstract

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.ResultsWe 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.ConclusionsThe 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.

Arabic linked drug dataset consolidating and publishing

“…One of the first linked data methodologies was developed in the European research project LOD2 (Creating Knowledge out of interlinked Data, 2011-2014) 22 that was mainly dedicated to the publishing process, i.e., opening data in a machine-readable format and establishing the tools and technologies for interlinking and integrating heterogeneous data sources in general. Jovanovik and Trajanov [17] concluded that "the LOD2 methodology which provides software tools for the denoted steps still misses some key elements of the linked data lifecycle, such as the data modeling, the definition of the URI format for the entities and the ways of publishing the generated dataset". They also stated, "The LOD2 tools are general, and cannot be applied in a specific domain without further work and domain knowledge."…”

“…Before converting XLS data to RDF, the authors selected the target ontology to describe the drugs contained in the drug availability dataset. Authors selected the LinkedDrugs 23 ontology [17], Schema.org vocabulary, and DBpedia, as they have the needed properties and provide easier interlinking possibilities for further transformation. The Web Ontology Language allows complex logical reasoning and consistency checking for RDF and OWL resources.…”

Computer Information Systems and Industrial Management

“…opening the data in a machine-readable format and establishing the prerequisite tools and technologies for interlinking and integration of heterogeneous data sources in general. Jovanović and Trajanov [10] proposed a new Linked Data methodology with a focus on reuse which provides guidelines to data publishers on defining reusable components in the form of tools and schemas/services for the given domain (i.e. drug management).…”

“…Before converting XLS data to RDF, the authors selected a target ontology to describe the drugs contained in the drug availability dataset. Authors selected the LinkedDrugs ontology [10], Schema.org vocabulary, and DBpedia, as they have the needed properties and provide easier interlinking possibilities for further transformation. The Web Ontology Language allows complex logical reasoning and consistency checking for RDF and OWL resources.…”

Modelo de infraestrutura para publicação de dados abertos governamentais conectados de qualidade

“…Na literatura científica, algumas metodologias para publicação de dados abertos governamentais conectados foram propostas, mas os adotantes afirmam que elas são muito genéricas para seus propósitos, com poucos estudos detalhando o processo como um todo, sem diretrizes para ferramentas de software, modelos de documentos, técnicas ou outros artefatos que possam ajudá-los na adoção desta tecnologia (LAESSIG;JACOB;ABOUZAHR, 2019;JOVANOVIK;TRAJANOV, 2017;BOSELLI et al, 2014;SANTOS, 2014). Como consequência, muitos produtores não possuem conhecimento suficiente dessas recomendações e propõem métodos ad-hoc para produzir dados abertos conectados (SANTOS et al, 2018), geralmente baseados somente nos princípios básicos dos dados conectados (BERNERS-LEE, 2006).…”