Home Implementation Networks Current Implementation Networks Virus Outbreak Data Network (VODAN)

The GO FAIR Office is currently experiencing significant increase in support requests due to high interest in the VODAN Implementation Network. While we are excited to see such enthusiasm in the data community, the office staff capacity is limited. If you need to contact us, please email us at office@go-fair.org and we will do our best to respond in a timely manner. Thank you for understanding. Additional contacts for projects and sub-teams will be announced soon.

Active GO FAIR Implementation Network
The spread of the virus causing the COVID-19 outbreak is far from over. During this epidemic and in earlier occasions, we have seen severely suboptimal data management and data reuse. Moreover, access to the immensely valuable data of past and current epidemics is not always equally accessible for different affected populations and countries. For instance, the data from the past Ebola epidemics are very difficult to find, to access, and if accessible, they are not interoperable, let alone reusable. In the case of Ebola this is even more harrowing and ironic as the data are least available to the population that were most affected by the disaster. Under the urgent need to harness machine-learning and future AI approaches to discover meaningful patterns in epidemic outbreaks, we need to do better and ensure that data are FAIR (in this sense also meaning Federated, AIReady).

This Implementation Network is part of the joint activities carried out by CODATA, RDA, WDS, and GO FAIR under their Data Together statement, working to consolidate and make explicit the key role for each of the internationally operating data organisations and in particular to bring CODATA, RDA, WDS, and GO FAIR even closer together, with clear and complementary mandates.

Purpose of the Implementation Network
This time, we can do better. We now have the technical ability, as well as the commitment from experts in a series of affected countries, to make the SARS CoV-2 virus data FAIR, meaning that they are Findable, Accessible, Interoperable and thus Reusable by both humans and machines, during this epidemic of COVID-19. The technical components that make this possible can remain in place, waiting in ready state for potential future infectious disease outbreaks.

We started this Implementation network with a very narrow focus, based on seed funding from co-founding partners, ZonMW and the Philips Foundation (see the manifesto), namely to make source data FAIR and make them available for reuse in a distributed manner. With a sense of urgency driven by the rapid developments on COVID-19  we came together to  launch a GO FAIR Implementation Network to address the immediate challenges. For this epidemic, unfortunately, we have to ‘FAIRify’ COVID-19 data ‘after the fact’ and use Chinese, Dutch, Swedish, etc. and English electronic (or even hand-written) health records to create proper FAIR data. The FAIRification will initially focus on the Clinical Research Form (CRF) model following the WHO standards. Multiple IN partners will create input forms that make it easy for local caregivers to create FAIR-CRF data in real time as a first step. As a second step, we will jointly develop (via online work sessions) localized FAIR Data Points (FDP). FDP is a FAIR data repository with ‘docking’ capabilities as a ‘station’ for ‘trains’ (virtual machines (VMs)) that come to ‘visit’ the data locally, with a specific question to ask. The local data custodian (frequently a hospital or centre for disease control and prevention type of institution) grants permission to VMs to ask the question / run analyses. As the personal data of patients never leaves the underlying database of the local institution, GDPR issues are largely accommodated and in this way data can be ‘shared’ or rather ‘visited’ without violating any patient rights and, in the case of a disease outbreak, also governed by the laws and policies of the individual jurisdictions in which the outbreak manifests.

Trains (VMs) can visit multiple local FAIR Data Points to get their questions answered. For more information on the underlying technological approach please visit the Personal Health Train IN pages. The data stewardship aspects of FAIR data will be addressed wherever possible with the Data Stewardship Competence Centres IN.

Targeted Objectives
The VODAN IN consortium is a light-weight public private partnership (members listed below) that will jointly address in a stepwise fashion, the following issues:

  • Ensure that the WHO-CRF(s) and other input forms for Corona data (and later viral outbreaks in general) are properly mapped to a machine readable (RDF) format, so that any stakeholder can create input forms that lead to the resulting data being a machine actionable (FAIR) digital objects.
  • Create multiple user-friendly input systems (e.g., web forms) that create interoperable (FAIR) data ‘upon save’. Castor, one of the IN members, already took a first step.
  • Assist partners in affected regions to use traditional source files to create FAIR versions of selected data available in their country with local experts (domain experts, EHR experts and Semantic Data experts), mainly with Online Collaboration sessions.
  • Install, jointly with the local partners, a local FAIR Data Point (FDP) -or multiple points, in case the data are not centrally collected in the country. Again, this is a remote working session, as an FDP is a server application that can be installed in partnership with local institutions, according to the local specifications and in compliance with regional laws.
  • Deliver, with the partners in the participating countries, a series of FDPs that can be ‘visited’ under well-defined conditions by VMs (trains) to answer questions and discover patterns in these ‘real world observation data’. (Note: this will not yet be a fully automated distributed learning environment)
  • Demonstrate the value of this approach to WHO and other (national and international authorities and initiatives such as GLOPID-R) and seek certification and WHO approval for FAIR compliant CRF forms, FDPs and access protocols that do not violate personal privacy and/or national legislation.
  • Advanced stage: Develop a FAIR conceptual model for viruses and viral outbreaks originally based on CRFs and the sort of data CDC/RIVM-type institutions typically collect.
  • Offer the ‘Real World Data’ FDPs under agreed conditions to qualified research groups, institutions and private companies to use the data (by controlled querying, not downloading) to answer questions that may lead to the discovery of patterns in real world and established knowledge data, which in turn may lead to new prevention and intervention options.
  • As a final step before the IN will dissolve and hand over its assets to either standing organisations or a new, larger IN dealing with a wider approach to real world data FAIRness (in a preparatory phase now), including registries of vaccines drugs, side effects etc, the consortium will document and publish in Open Access and under CC-by license, all specifications that allow future repetition of this process for new epidemics that will undoubtedly confront society with similar challenges.

Expectation management statement
This IN will NOT include the actual research projects that may make use of the FAIR Data Point network created. Third parties (that may or may not include partners also participating in the VODAN IN) will be able to gain access to the data under the conditions set by the data custodians and/or WHO. FAIR data form a substrate for machine-assisted research and are not a solution or a goal in themselves. In addition, the IN itself will not be able to sustain, or expand the service beyond its initial activity and funding cycle. It is therefore crucial that on ‘day one’ a scalability and sustainability model of the services will be developed by the partners.

Manifesto
Link to manifesto in PDF

Contact
Bert Meerman, GO FAIR Foundation
Barend Mons, GO FAIR International Support and Coordination Office (interim coordinator)

Are you interested in joining VODAN? Please express your interest by filling in the form below. 

After filling out the above subscribe form, names will be added to the partners list manually twice a day. More partners are expected to join the IN over next few weeks.

Partners – active IN contributors

Name Affiliation
Aliya Aktau LIACS, Kazakhstan
Arie Baak Euretos AI Platform
Mariam Bassajja LIACS, PhD – coordinator
Oya Beyan Fraunhofer FIT
Margreet Bloemers ZonMw, FAIR data management
Quirine ten Bosch Infectious Disease Epidemiologist at Wageningen University and Research
Paolo Budroni TU Wien
Stuart Chalk University of North Florida
Kudakwashe Chindoza LIACS, Zimbabwe
Nikola Cihoric niAnalytics
Ben Companjen Leiden University Libraries
Frederick Fenter Frontiers (open-access publisher)
Leone Flikweert NL-Health-RI – enabling data driven health
Wouter Franke Zorginstituut Nederland
Giancarlo Guizzardi Free University of Bozen-Bolzano, Italy
Vibhor Gupta Pangaea Data Limited
Leontios Hadjileontiadis Aristotle University of Thessaloniki, Greece; Khalifa Ubiversity, Abu Dhabi, UAE
Jaap Heringa ELIXIR-NL
Kristina Hettne Leiden University Libraries
Simon Hodson CODATA
Peter-Bram ‘t Hoen Radboud university medical center
Andreas Ingvar van der Hoeven Öökull BV
Esther Inau Universitätsmedizin Greifswald, Germany
Annika Jacobsen Leiden University Medical Center
Mascha Jansen GO FAIR Foundation
Rajaram Kaliyaperumal LUMC
Clint de Keizer Rebel Group
Martijn Kersloot Castor EDC and Amsterdam UMC, Univ. of Amsterdam
Christine Kirkpatrick San Diego Computer Center, University of California San Diego
Hylke Koers SURF
Oliver Kohlbacher University of Tuebingen, ELIXIR-Germany
Ruben Kok DTL – Dutch Techcentre for Life sciences
Dimitris Koureas DiSSCo / Naturalis Biodiversity Center
Racheli Kreisberg Israeli-Dutch Innovation Center, Netherlands Embassy in Israel
Tobias Kuhn VU Amsterdam
Yann Le Franc e-Science Data Factory
Paul Lee Hong Kong Polytechnic University
Stefan Leijnen Utrecht University of Applied Sciences
Brane Leskošek ELIXIR-SI
Bert Meerman GO FAIR Foundation
Barbara Magagna Environment Agency Austria
Les Mara Databiology Ltd.
Stanton Martin Oak Ridge National Laboratory
Natalie Meyers Navari Family Center for Digital Scholarship, University of Notre Dame
Martin van Mierloo Luminis Technologies
Deepti Mittal Heidelberg Pain Consortium, Heidelberg University, Germany
Albert Mons Phortos Consultants, FAIR Solutions
Joao Moreira University of Twente
Erik van Mulligen ErasmusMC / Science and Technology Corporation
Mark Musen Stanford University (CEDAR)
Narges Norouzi UC Santa Cruz
Rutger Nugteren Data and information manager
Amelia Palermo University of California
Robert Pergl Czech Technical University in Prague, Codevence
Tiago Prince Sales Free University of Bozen-Bolzano
Putu Hadi Purnama Jati LIACS, Indonesia
Eduardo Quemada Fair Data Systems, FAIR solutions, Spain
Mirjam van Reisen Leiden University, Tilburg University, The Netherlands
Marco Roos LUMC Biosemantics group and RDs GO FAIR
Gerbrand Ruiter Mobiquity – and personal
Alena Rybkina CODATA
Folkert Saathoff Databiology Ltd.
Bruna dos Santos Vieira Data Steward (Radboudumc, VASCERN, EJPRD)
Venkata Satagopam LCSB, University of Luxembourg and ELIXIR-Luxembourg Node
Juliane Schneider Harvard Catalyst
Luke Smith Databiology Ltd.
Marc Teunis University of Applied Science – Hogeschool Utrecht
Erik Tews University of Twente, Netherlands
Inga Tharun Personal Health Train Consortium
Viviane Veiga Fiocruz/GO FAIR Brazil Health
Jiri Vondrasek ELIXIR CZ
Danielle Welter LCSB, University of Luxembourg and ELIXIR-Luxembourg Node
Mark Wilkinson Universidad Politecnica de Madrid
Peter Wittenburg Max Planck Computing & Data Facility, C2CAMP & GEDE CO-Chair
Qiqi Zhang LIACS, China
Johan van der Zwart NTNU, Norwegian University of Sience & Technology

Partners – observers

Name Affiliation
Ramamohana Reddy Appannagari CHEMTEX Environmental Laboratory.inc
Bo Nygaard Bai Aalborg University
Anders Conrad DeiC
Katrine Düring Davidsen Aarhus University Library
Rens van Erk Data analyst
Martin Ingvar Karolinska Institutet, Stockholm, Sweden
Getu Tadele Getu Mekelle University
Samuel Kerrien EPFL – Blue Brain Project
Karsten Kryger Hansen Aalborg University
Malcolm Macleod CAMARADES
Wondimu Manamo Addis Ababa University
Caroline Nassali Attached to Ministry of Health Uganda
Lars Nondal Copenhagen Business School
Marc Nyssen ISC/WDS Scientific Committee
Karen Payne ISC/WDS
Øivind Riis Østfold Hospital Trust, Norway
Niek van Ulzen Amsterdam University of Applied Sciences
Angela Putignano
Barbara Sánchez TU Wien
Gary Saunders ELIXIR
Ben Schaap Wageningen University and Research
Seth Schimmel CUNY / Open Society Foundations
Mohameth François Sy EPFL, Blue Brain Project, Switzerland
Suzanne Verver ZonMw, programme Infectious diseases
Anna Wałek Gdańsk University of Technology, Poland
Marcin Wojewodzic University of Birmingham