FAIR HEALTH DATA SHARING INITIATIVES IN EUROPE

OPPORTUNITIES AND CHALLENGES FOR INTERNATIONAL COOPERATION

Prof. Dr. Hans-Ulrich ProkoschChair of Medical Informatics, University of Erlangen-Nuremberg

CIO of Erlangen University

Coordinator of the MII MIRACUM Consortium

FAIR HEALTH DATA SHARING INITIATIVES IN EUROPE:

OPPORTUNITIES AND CHALLENGES FOR INTERNATIONAL COOPERATION

The Workshop Team

Hans-Ulrich Prokosch, Thomas Ganslandt, Ulrich Sax, Christian Lovis, Carlos Luis Parra Calderón, Nigel Hughes,

Peter Rijnbeek, Wiro Niessen Barend Mons, Kees van Bochove, Francisco J. Núñez Benjumea, Leila Alexander

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FAIR Health Data Sharing Initiatives in Europe

Workshop Agenda

• 13:00 Short Welcome, Introduction into the WS Agenda and the FAIR principles

• Ulli Prokosch, Chair of Medical Informatics, University of Erlangen-Nürnberg

• 13:15 Towards FAIR Data Sharing in the German Medical Informatics Initiative

• Thomas Ganslandt, Department of Biomedical Informatics of the Heinrich-Lanz-Center, Mannheim University Medicine

• 13:35 A Portfolio of Interconnected Shared Services to be FAIR in Health RI

• Wiro Niessen, Department of Medical Informatics, Erasmus MC

• 13:55 The EHDEN Project: Making European Data FAIR by Standardising to the OMOP Common Data Model

• Peter Rijnbeek; Department of Medical Informatics, Erasmus MC

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The FAIR principles and theFAIRification Process

The FAIR Data Principles apply to

• data (or any digital object),

• metadata (information about that digital object), and

• supporting infrastructure (e.g., search engines).

• Most of the requirements for Findability and Accessibility can be achieved at the metadata level.

• Interoperability and Reuse require more efforts at the data level.

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The FAIR principles and theFAIRification Process

The FAIR Data Principles apply to

• data (or any digital object),

• metadata (information about that digital object), and

• supporting infrastructure (e.g., search engines).

• Most of the requirements for Findability and Accessibility can be achieved at the metadata level.

• Interoperability and Reuse require more efforts at the data level.

The FAIRification process adopted by GO FAIR

• focuses on data,

• but also indicates the required work for metadata

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The FAIR principles and theFAIRification Process

Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJ, Groth P, Goble C, Grethe JS, Heringa J, 't Hoen PA, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar 15;3:160018. doi: 10.1038/sdata.2016.18.

FindableThe first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services.

F1. (Meta)data are assigned a globally unique and persistent identifier

F2. Data are described with rich metadata (defined by R1 below)

F3. Metadata clearly and explicitly include the identifier of the data they describe

F4. (Meta)data are registered or indexed in a searchable resource

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The FAIR principles and theFAIRification Process

Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJ, Groth P, Goble C, Grethe JS, Heringa J, 't Hoen PA, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar 15;3:160018. doi: 10.1038/sdata.2016.18.

AccessibleOnce the user finds the required data, she/he needs to know how can they be accessed, possibly including authentication and authorisation.

A1. (Meta)data are retrievable by their identifier using a standardised communicationsprotocol

A1.1 The protocol is open, free, and universally implementable

A1.2 The protocol allows for an authentication and authorisation procedure,where necessary

A2. Metadata are accessible, even when the data are no longer available

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The FAIR principles and theFAIRification Process

Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJ, Groth P, Goble C, Grethe JS, Heringa J, 't Hoen PA, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar 15;3:160018. doi: 10.1038/sdata.2016.18.

InteroperableThe data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.

I1. (Meta)data use a formal, accessible, shared, and broadly applicable language forknowledge representation.

I2. (Meta)data use vocabularies that follow FAIR principles

I3. (Meta)data include qualified references to other (meta)data

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The FAIR principles and theFAIRification Process

Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJ, Groth P, Goble C, Grethe JS, Heringa J, 't Hoen PA, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar 15;3:160018. doi: 10.1038/sdata.2016.18.

ReusableThe ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.

R1. Meta(data) are richly described with a plurality of accurate and relevant attributes

R1.1. (Meta)data are released with a clear and accessible data usage license

R1.2. (Meta)data are associated with detailed provenance

R1.3. (Meta)data meet domain-relevant community standards

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The FAIR principles and theFAIRification Process

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Turning FAIR into Reality

https://publications.europa.eu/en/publication-detail/-/publication/7769a148-f1f6-11e8-9982-01aa75ed71a1/language-en/format-PDF/source-80611283

• Concepts for FAIR

• Research Culture and FAIR

• Technical Ecosystem for FAIR data

• METRICS for FAIR data

• Assessment Frameworks to CertifyFAIR Services

• . . . . .

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FAIR Health Data Sharing Initiatives in Europe

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FAIR Health Data Sharing Initiatives in Europe

Workshop Agenda

• 13:00 Short Welcome, Introduction into the WS Agenda and the FAIR principles

• Ulli Prokosch, Chair of Medical Informatics, University of Erlangen-Nürnberg

• 13:15 Towards FAIR Data Sharing in the German Medical Informatics Initiative

• Thomas Ganslandt, Department of Biomedical Informatics of the Heinrich-Lanz-Center, Mannheim University Medicine

• 13:35 A Portfolio of Interconnected Shared Services to be FAIR in Health RI

• Wiro Niessen, Department of Medical Informatics, Erasmus MC

• 13:55 The EHDEN Project: Making European Data FAIR by Standardising to the OMOP Common Data Model

• Peter Rijnbeek; Department of Medical Informatics, Erasmus MC

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FAIR Health Data Sharing Initiatives in Europe

Workshop Agenda

• 14:35 From Raw Data to FAIR Ddata: FAIR4Health Vision

• Francisco J. Núñez Benjumea, Instituto de Biomedicina de Sevilla

• 13:15 A FAIRy Tale with BioMedIT and SPHN

• Leila Alexander, COO, Personalized Health Informatics Group, SIB Swiss Institute of Bioinformatics

• 13:35 Convergence of Research and Care Networks in the Swiss Health System

• Christian Lovis, Chairman, Division of Medical Information Sciences; University Hospitals and University of Geneva

• 13:55 Supporting FAIR Developments from a Business Perspective

• Kees van Bochove, The Hyve

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Acknowledgements

• MIRACUM is funded by the German Federal Ministry of Education and Research (BMBF) within the Medical Informatics Funding Scheme (FKZ 01ZZ1606A-H).

• HiGHmed is funded by the German Federal Ministry of Education and Research (BMBF) within the Medical Informatics Funding Scheme (FKZ 01ZZ1802B-X).

• FAIR4Health has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824666.

• EHDEN is funded by the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 806968. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.

• Christian Lovis receives Swiss Personalized Health Network initiative funding 2017DEV10, 2017DEV12 and 2017DEV15.