Here we provide information about open science, open access publications and FAIR data stewardship aiming at the research community that works on the current COVID-19 outbreak. The information is also a guidance for ZonMw’s requirements and recommendations in its research programmes for COVID-19. It addresses the following research activities:

  1. Transparency on research projects
  2. Creating FAIR data
  3. Access to research data
  4. Sharing of research findings through open access publications

For these research activities, we point in the sections below to the latest developments for FAIR data management and stewardship.

The overall aim is to synergize the many efforts in the current hectic of COVID-19 research, to benefit from new developments, to find options to collaborate, and to prevent double work.

Update on ZonMw’s approach to optimize reuse of COVID-19 related data

Under the urgency of the outbreak of the corona pandemic, we take a number of actions to enable researchers in ZonMw’s COVID-19 projects to create FAIR data or - as a minimum - FAIR metadata that can be used by humans as well as machines. As a result, data and metadata become findable through computer search, and ready for access with learning-algorithms (comparable to the Personal Health Train concept).

This approach allows other research on COVID-19 to directly benefit from ZonMw’s projects, accelerating solutions for the corona crisis.  

These activities include:

All focus areas in the ZonMw COVID-19 programme

The activities are intended for all COVID-19 projects that ZonMw has granted funding in 2020. They are part of data management planning as required for ZonMw funded projects. The activities for creating FAIR data and metadata will be organised for clusters of projects with similar topics, subdisciplines, and/or methods and techniques. Creating FAIR data will therefore be tailored to quantitative as well as qualitative research; biomedical, behavioral, and social economic research, or any other discipline in ZonMw’s COVID-19 programme. 

Data experts, domain experts and their research communities

A crucial aspect of the FAIRification approach is that domain experts (researchers) collaborate with data experts. In clusters of projects with similar topics (etc), they form research communities. They decide on the standards, technologies, and infrastructure that fit in their research area best. These are then captured in community specific metadata schemes that researchers can apply in their projects, and show in their DMPs.

Support and community building

For creating FAIR data and metadata, the data stewards and researchers of the COVID-19 projects receive training and support from FAIR data experts at GO FAIR and Health-RI. They therefore organise a number of workshops and training in autumn 2020. The dates can be found here.

In addition, the DTL Data steward Intrerest Group organises support and community building for local data stewards to exchange ideas, and solve challenges.

Select for more information about:

  1. What researchers need to do for a grant proposal and research project
  2. Transparency and sharing of research findings and data
  3. Creating FAIR data, tailored to the COVID-19 research community

Read more about:

Guidance

Networks, data services

  • VODAN, Viral Outbreak Data Network, to create FAIR (and machine readable) (meta)data, e.g. with the COVID-19 case record form (CRF) of the WHO (see GitHub and BioPortal, Castor).More on these and other VODAN deliverables (summer 2020).
  • VODAN-in-a-box, a toolset to facilitate the capture of data related to virus outbreaks and the publication of metadata describing these datasets. The resulting infrastructure makes real world COVID-19 patient data available for research, under well-defined conditions and with patient privacy well protected.
  • Health-RI, COVID-19 related initiatives
  • Genotyping COVID-19 patient DNA (see Genetic laboratory of ErasmusMC)
  • COVID-19 HOTEL@ DTL serves COVID-19 projects to rapidly rationalise phenomena observed in real world situations, generate hypotheses that can be laboratory tested, and subsequently serve decision making in the clinical setting. The COVID-19 Hotel enables an in silico rationalisation workflow, making use of FAIR data.
    COVID-19 HOTEL@ DTL

Portals to find projects, data and other resources

COVID-19 related research initiatives

REMAP-CAP uses an innovative trial design to efficiently evaluate multiple interventions simultaneously (see also the webinar session 4, May 7 2020)

CAPACITY and the FAIR data project (statistical analyses and machine learning models for insights about the relation between cardiovascular history and related complications in COVID-19 patients)

Please inform us about more other COVID-19 research and FAIR data initiatives: toegangtotdata@zonmw.nl

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