Dear GO FAIR community,
In this editorial we focus on the use of FAIR data and approaches in the scope of the ongoing COVID-19 Global crisis. The current situation proves that FAIR is not only of great relevance within science, but also meets a very real need beyond science. We have therefore asked Erik Schultes to share with our community the developments in our COVID-19 related Implementation network VODAN, and specifically also its spin-off for other GO FAIR Implementation Networks as well as the upcoming CODATA/GO FAIR symposium. His contribution follows:
The Virus Outbreak Data Network (VODAN) finalised its manifesto March 10, the day before the WHO declared that COVID-19 can be characterized as a pandemic. With a sense of urgency that continues to stimulate its members 6 months later, the VODAN IN set out to find practical implementations making SARS CoV-2 virus data more Findable, Accessible, Interoperable and thus Reusable for humans and for their machine assistants. Although we might anticipate that FAIR data and services could in general help mitigate the COVID-19 pandemic, VODAN’s stated objectives are to have mature FAIR capabilities at the ready, in preparation to manage the inevitable infectious disease outbreaks of the future.
The VODAN IN was launched with two small projects having very similar, and very prescribed goals: Install a FAIR range of distributed data repositories hosting a machine-actionable version of the World Health Organisation’s standard COVID-19 Case Report Form. A key objective was to demonstrate that COVID data can be made available for analytics without having to be copied or moved from the location where it was originally collected. This allows the data (especially privacy-sensitive data) to remain at all times in the custodianship of the data producers. In one of the projects, funded by the Dutch ZonMW, the FAIR repository was to be set up in the Leiden University Medical Centre in The Netherlands, while the sister project funded by the Phillips Foundation targeted the medical centre of Kampala International University (KIU) in Uganda. The African project soon expanded to five other African countries now composing the VODAN Africa project.
With haste, collaborative teams within the GFISCO, LUMC and KIU went into action deploying FAIR tools and practices that were already available, and rapidly developed other resources so as to create a complete, real-world FAIRification process that would be easily replicable by others. On July 22 Mariam Basajja, a PhD student from Kampala International University and Leiden University, launched the first VODAN FAIR Data Point. This was followed in rapid succession by two VODAN FAIR Data Points in Nigeria and now others in Ethiopia, Tunisia, Kenya and Zimbabwe (VODAN Africa timeline). On August 31, the LUMC FAIR Data Point went on line, and two days later on September 2, a Technical Session was held between Leiden University Medical Center and VODAN Africa teams to initiate the discussions leading to the documentation of specifications for the VODAN FDP and the demonstration of inter-continental query.
What has emerged in VODAN is the beginnings of a FAIR data network that could find widespread reuse in other regions and in other topical domains. This practical, project-driven FAIRification approach has now been encapsulated as the 3-Point FAIRification Framework, which is proving to be as effective in communication as it is in deployment. For example, the 3-Point FAIRification Framework is now finding application in the larger Dutch National COVID-19 Research Program, where individual research projects will be using Metadata for Machine Workshops, contributing to FAIR Implementation Profiles and launching potentially many more FAIR Data Points to publish FAIR research outputs. Although the disruption and fatalities of the pandemic leave their impact on all of us, the streamlining of FAIR implementation we witness in VODAN will leave us much better prepared for future outbreaks and could be reused for many other FAIR applications.
The 3-Point FAIRification Framework will guide several domain communities to drive their FAIRification efforts in preparation for the FAIR Convergence Symposium. Series of practical workshops are being organised with enthusiastic early-mover communities. An initial Orientation meeting to provide background on the 3-Point FAIRification Framework will be held on 21 September and will be recorded.
All the best,
Laurent Crouzet, Barend Mons & Klaus Tochtermann
Strategic Directors, GO FAIR Initiative
Did you know… GO Read
In this section you will learn about Implementation Networks that have recently acquired “active” status, recent IN activities and opportunities. This way, we ensure that you always stay on top of things happening in the “GO FAIR” family.
New “active” GO FAIR Implementation Network:
The AdvancedNano IN aims to advance innovation in nanoscience while improving human health and the environment through a shared infrastructure to support the generation, management, analysis, and (re)use of data. This AdvancedNano IN gathers key players in nanosafety data, such as data generators, database developers, data(base) users and regulators/policy makers, who take steps to make their datasets and databases FAIRer. IN Coordinators are Martine Bakker from the National Institute of Public Health and the Environment (RIVM) and Blair Johnston from the German Federal Institute for Risk Assessment (BfR).
Reports from internal events
- The CO-OPERAS IN published the reports of all the workshops organized in the past year on the topic of “FAIR data for Social Sciences and Humanities” on Zenodo.
- Giovanni Pizzi, IN Coordinator of the Materials Cloud IN, and collaborators successfully held a virtual tutorial for AiiDA and the Materials Cloud that attracted 85 participants from all over the world. The tutorial and full report of the event were made available. Moreover, two publications about the Materials Cloud and AiiDA just got published in Nature Scientific Data: Materials Cloud, a platform for open computational science & AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance.
- International FAIR Convergence Symposium (30 November – 04 December 2020, virtual): Submit your proposals for sessions by 30 September 2020, and for posters and lightning talks by 31 October 2020!
- Register for the virtual 2020 Annual Meeting on 14-16 October 2020 by the Academic Data Science Alliance (ADSA), a newly launched initiative to advance the uptake of data science best practices in higher education.
- Computable Award: The Personal Health Train is one of five nominated projects! Vote now for your favourite project! (Deadline: 1st November 2020)
Interesting reads from the INs
- The VODAN IN informs: “COVID-19 Computer-Readable Observational Data Installed at Kampala International University”. Following the installment of the first FAIR Data Point, a second FAIR Data Point was installed in Data Science Nigeria and a third FAIR Data Point in at Ibrahim Badamasi Babangida University in Nigeria.
- Read the paper by Romain David (member of the BiodiFAIRse, VODAN & Food Systems IN), Laurence Mabile (BiodiFAIRse IN member), Clement Jonquet (Food Systems IN member) & Yvan le Bras (one of the coordinators of the BiodiFAIRse IN) et al.: “FAIRness Literacy: The Achilles’ Heel of Applying FAIR Principles” published in the Data Science Journal.
To enhance treatment of data according to the FAIR principles, we suggest that organisations should be assessed on the basis of how well they support their researchers in becoming FAIR advocates.
This section gives you an overview of conferences and workshops where you can meet up (virtually) with fellow GO FAIR members if you happen to attend the same event or are in the same town.
In order for this category to work we do need your help! Please drop us a line at firstname.lastname@example.org and tell us where you can be met in the future.
- 28 September – 02 October 2020 (virtual): Say hello to Barend and Erik (GFISCO), and Claudio, Ronald, Esther, Gulcin, Marc, Rajaram, Marco and Mark from the Rare Diseases IN at the International Summer School on Rare Diseases Registries and FAIRification of Data.
- 27 October 2020, Genua (Italy): Meet Barend (GFISCO) at the Festival della Scienza.
- 03-06 November 2020, Vienna (Austria): Meet Luiz (GFISCO) and IN representatives Peter (GO Inter), Barbara (GO Inter), João Moreira (GO Inter) and Robert Pergl (VODAN, GO Inter, FAIR StRePo) at the 2nd Workshop on Conceptual Modeling, Ontologies and (Meta)data Management for FAIR Data. Submit your paper by 27 July 2020.
- (NEW DATE) 27 November-04 December 2020, virtual: International FAIR Convergence Symposium & CODATA General Assembly convened by GO FAIR and CODATA.
People of GO FAIR
In this section we would like to introduce you to members of our GO FAIR family. In each newsletter we will provide you with a short profile of two GO FAIR members.
Oya Beyan, Andre Dekker, Oliver Kohlbacher, IN Coordinators of the Personal Health Train IN
|Oya Beyan is Deputy Head of the Department “Knowledge Pipelines” at Fraunhofer Institute of Applied Technology and leader of the team “FAIR Data and Distributed Analytics ”. She conducts research related to data reusability and FAIR data management, distributed analytics on sensitive data, and data-driven transformation in medicine. Her ambition is to achieve semantically interpretable machine actionable data and services to foster data-driven science and industry, without compromising fairness, equity, privacy, and confidentiality of individuals as well as social groups and communities. Oya serves as a member of the EOSC FAIR Working Group and RDA Germany and co-coordinates the GO FAIR Personal Health Train Implementation Network.|
|Andre Dekker is a medical physicist and Professor of Clinical Data Science at Maastro Clinic and Maastricht University Medical Center in The Netherlands. His Clinical Data Science research group (30 staff) focuses on three main themes: 1) building privacy-preserving, global data sharing infrastructures; 2) using artificial intelligence to learn health prediction models from this data; and 3) applying prediction models to improve health and health decisions for individual patients. Andre has authored over 150 publications in peer reviewed journals covering informatics, imaging, radiotherapy, tissue optics and heart disease and holds multiple awarded patents. He has held visiting scientist appointments at organizations in the UK, Australia, Italy, USA and Canada.|
His research encompasses method development and applications of algorithms for the analysis of high-throughput data and clinical data.
Executive Board representative:
|Susanna-Assunta Sansone is an Associate Director, Associate Professor and Principal Investigator at the Oxford e-Research Centre, part of the Department of Engineering Science at the University of Oxford. Her Data Readiness Group researches and develops methods and tools to improve data reuse, for data transparency, research integrity and the evolution of scholarly publishing. Susanna is one of the authors of the FAIR principles paper and an active (co)leader to a variety of community-driven FAIR-enabling efforts, one of them being FAIRsharing.org. As a curated resource on data and metadata standards, repositories as well as data policies, FAIRsharing is among the few flagship outputs of the Research Data Alliance; it is endorsed by a variety of stakeholders and also serves as a key platform of the FAIR StRePo IN, where Susanna and her co-lead Peter McQuilton aim to help other GO FAIR INs promote their output and better reach relevant stakeholder communities.|
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