First steps towards data FAIRification in COVID-19 research

In March 2020, during the early onset of the COVID-19 pandemic, ZonMw, GO FAIR Foundation and Health-RI became aware of the urgent need to make research projects and data that are produced and used findable and reusable through computer assisted, online queries. They realised that online transparency on projects and data is a crucial condition to accelerate knowledge development for fast solutions for the pandemic. Moreover, they decided that such transparency can only be achieved by following the FAIR principles to make research outputs findable, accessible, interoperable and reusable, not only for people, but also for machines (computers).

Unique collaboration

ZonMw as a funding agency, and the FAIR data experts at GO FAIR Foundation and Health-RI organised a unique collaboration to develop a workflow, tools and a data portal to produce and use FAIR-metadata and -data. They organised workshops with researchers and data stewards of the ZonMw-funded COVID-19-projects, who could provide relevant ‘domain information’ about topics and terms related to COVID-19, as well as standards, protocols (etc) in this research area. Their efforts resulted – as described below - in FAIR metadata schemes (M4M) to capture information (=metadata) about projects and data.

FAIR data need FAIR metadata!

For the online querying of data (‘data visiting’) from different studies and sources on specific topics (such as COVID-19) it is necessary that the computer can find, understand and use the data. The FAIR principles are the guide to realise this condition. A crucial step is to produce machine-actionable metadata, which contain all the information that the computer needs therefore. We now have tools and a workflow to produce machine-actionable metadata about the projects and data in COVID-19 research.

Tools, services and infrastructure: metadata-for-machines

ZonMw, GO FAIR Foundation and Health-RI collaborated in 2020 to develop the tools and workflow to produce machine-actionable metadata (M4M) and datasets. The metadata are captured with CEDAR forms, which can be used as questionnaires, and have the technology (1) to make the metadata machine-actionable, and (2) to make use of controlled vocabularies for a standardised and machine-actionable description of the project and the data (in this case (COVID-19 specific) controlled vocabularies). Here one can find the guidelines, FAQs, vocabularies, and forms to produce metadata-for-machines for COVID-19 research projects and their databases.

Tools, services and infrastructure: multiple data portals

The machine-actionable metadata about COVID-19 projects and data, that are produced with the M4M forms, are exposed in a human-readable format on the COVID-19 data portal at Health-RI. The portal supports data search, find and request functionalities. Since 2023, the Health-RI COVID-19 resources are also visible on the European COVID-19 Data Platform. In this way, when Dutch researchers enter information about their databases in CEDAR forms, they can be found both in the national and the European database. 

Tools, services and infrastructure: VODAN

Also in 2020, and partly funded by ZonMw, GO FAIR Foundation initiated the Virus Outbreak Data Access Network (VODAN) to enable the actual querying of data (‘data visiting’). VODAN started by making the WHO Clinical Research Form (CRF) FAIR. That means that each element in the form can be filled in with terms from machine-actionable controlled vocabularies. A form that has been filled in like this, can be found, understood and used by machines. The VODAN use case makes use of FAIR data point (FDP) software to capture metadata and enable data entry. This package for producing and using FAIR clinicaldata is available for other users through the VODAN-in-a-Box toolset.

The VODAN-approach was implemented in Africa in 9 countries, involving many hospitals and universities, realising an internet of FAIR data that can be queried. It may be considered as the first successful demonstration of FAIR data visiting. Further implementations are taking place in VODAN Africa and Asia.

You can read more about data FAIRification at FAIR data background, GO FAIR Foudation and Health-RI, and in Spinoffs from COVID-19 data FAIRification.