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      FAIRification of health-related data using semantic web technologies in the Swiss Personalized Health Network

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          Abstract

          The Swiss Personalized Health Network (SPHN) is a government-funded initiative developing federated infrastructures for a responsible and efficient secondary use of health data for research purposes in compliance with the FAIR principles (Findable, Accessible, Interoperable and Reusable). We built a common standard infrastructure with a fit-for-purpose strategy to bring together health-related data and ease the work of both data providers to supply data in a standard manner and researchers by enhancing the quality of the collected data. As a result, the SPHN Resource Description Framework (RDF) schema was implemented together with a data ecosystem that encompasses data integration, validation tools, analysis helpers, training and documentation for representing health metadata and data in a consistent manner and reaching nationwide data interoperability goals. Data providers can now efficiently deliver several types of health data in a standardised and interoperable way while a high degree of flexibility is granted for the various demands of individual research projects. Researchers in Switzerland have access to FAIR health data for further use in RDF triplestores.

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          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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            Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers.

            The vision of creating accessible, reliable clinical evidence by accessing the clincial experience of hundreds of millions of patients across the globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from the Observational Medical Outcomes Partnership to turn methods research and insights into a suite of applications and exploration tools that move the field closer to the ultimate goal of generating evidence about all aspects of healthcare to serve the needs of patients, clinicians and all other decision-makers around the world.
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              BioPAX – A community standard for pathway data sharing

              BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.
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                Author and article information

                Contributors
                sabine.oesterle@sib.swiss
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                10 March 2023
                10 March 2023
                2023
                : 10
                : 127
                Affiliations
                [1 ]GRID grid.419765.8, ISNI 0000 0001 2223 3006, Personalized Health Informatics Group, , SIB Swiss Institute of Bioinformatics, ; 4051 Basel, Switzerland
                [2 ]Trivadis — Part of Accenture, 4051 Basel, Switzerland
                [3 ]GRID grid.8515.9, ISNI 0000 0001 0423 4662, Health Informatics and Data Privacy Group, Biomedical Data Science Center, , 1010 Lausanne University Hospital, ; Lausanne, Switzerland
                [4 ]GRID grid.412004.3, ISNI 0000 0004 0478 9977, Clinical Data Platform Research, Directorate of Research and Education, , Zurich University Hospital, ; 8091 Zurich, Switzerland
                [5 ]GRID grid.150338.c, ISNI 0000 0001 0721 9812, DSI - Data Group, , Geneva University Hospital, ; 1205 Geneva, Switzerland
                Author information
                http://orcid.org/0000-0003-2052-6133
                http://orcid.org/0000-0003-3248-7899
                Article
                2028
                10.1038/s41597-023-02028-y
                10006404
                36899064
                146a8366-65bb-4b9b-a39f-69cba1efcbfc
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 August 2022
                : 17 February 2023
                Funding
                Funded by: Swiss Personalized Health Network
                Categories
                Article
                Custom metadata
                © The Author(s) 2023

                health care,medical research
                health care, medical research

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