How data sharing has changed in the COVID-19 era 

The COVID-19 pandemic has created unprecedented challenges, uncertainty, and destabilization for researchers. With labs and work spaces temporarily shut down due to the imposed lockdowns, scientists had to adapt to new conditions, including conducting scientific projects at home. To respond to a public health emergency like COVID-19, easy access to essential relevant research and sharing data openly and quickly became a necessity. 

Watch the recording of our recent webinar, ‘’Open data in the COVID-19 pandemic’’ or read on to learn how the pandemic has affected researchers and data sharing practices. 

While the world closed, science opened  

Researchers increasingly used their own data and data from others 

The pandemic has caused significant disruption to the scientific process which has led to changing views on data reuse.  

The State of Open Data 2020 report surveyed authors worldwide on the impact of the pandemic on their research and research practices. Only 10% of authors surveyed indicated they could maintain all their work commitments. 32% stated that they were ‘extremely’ or ‘very’ impacted. This fueled an increase in the reuse of researchers’ own data and data from others. The scientific community adapted to the fact that they were not able to potentially collect all the data themselves. Instead, they focused on using openly available data — their own or others’. 

Use of pre-prints rose dramatically  

The pandemic drove a huge increase in open science practices. More than 30,000 pre-prints were published in 2020 globally. Many of them reported key discoveries that influenced health policy. These included early transmission data which fed into government policies around things like isolation periods. The rapid dissemination of such data was very beneficial at the early stages of the pandemic when we knew very little about the COVID-19.  

Immediate, easy access to data became crucial for informing responses in real-time 

As a result of the pandemic, most publishers made a commitment to ensure that any article being published on COVID-19 would be openly available. The Research on Research (RORI) institute reported that 88% of COVID-19 articles were published open access. The same report also demonstrated that 47% of respondents had made their COVID-19 data openly available. 

Open data has benefited the research community’s response to the pandemic. A very good example is the early and rapid sharing of the Sars-CoV2 genome back in January 2020. This enabled the quick manufacturing and testing of mRNA vaccines. 

Moreover, open data sharing has continued throughout the pandemic. The Wellcome Sanger Institute for instance, examines different variants across the UK through regular testing. Then, the Institute uploads all genetic data on its website for anyone to access and use. 

More work needed  

We have witnessed great progress in terms of open data and open science practices more generally throughout the pandemic, yet there is still more work to be done when it comes to data sharing. 

Only 4-6% of COVID-19 articles published during the pandemic had a corresponding pre-print. This means that the vast majority of authors followed the traditional route instead of rapidly disseminating their work.  

A study from Lucas-Dominguez et al. showed that of almost 6000 articles published from January to April 2020 only around 800 made their data available. Of these 800, only 1.2% were shared in a format that allowed reuse. Data were shared in a pdf or word document format and thus were not machine-readable.  

Furthermore, a study by Maxwell et al. also found that data sharing was concentrated in high-income countries. This raises questions of equity around opportunities to build expertise in data curation and sharing for research teams based in lower middle-income countries. 

It’s vital that we continue to encourage and educate researchers on open data sharing practices to find solutions to the challenges posed by COVID-19. 

Open data on F1000 

F1000 data policies  

F1000 advocates an open data policy. All articles on F1000 that report original results should include the source data underlying the results, together with details of any software used to process the results.  

F1000 also endorses the FAIR guiding principles as part of its open data policy. FAIR data is Findable, Accessible, Interoperable, and Reusable.  

The FAIR guidelines were published in Scientific Data in 2016, offering a new framework for research data management, designed to maximize its reuse and support open data practices. This goes beyond open data, aiming to make the data itself more useful and user-friendly, rather than simply ‘open’.

Benefits 

Open data is a key pillar of open research and presents several benefits. 

Firstly, having the data available alongside the underlying results and methodology reported aids reproducibility and transparency of reporting. Additionally, there are also practical benefits of sharing your data. A study by Colavizza et al. found that authors who employed open data practices could expect to see up to 25% increase in citations for their articles.  

Open data enables the reuse of data which has been crucial during the pandemic. It also helps to ensure that data scientists get the credit they deserve. Data scientists might not be included in the authorship of an article, but they can be included in the author list of a dataset.  

The pandemic has shone light on the need for and benefits of open science and open data practices. Together, researchers, publishers, and funders must learn from the successes and failures during the COVID-19 pandemic to foster practices that actively encourage and support open data going forward. 

For more information on open data sharing, visit our online hub of resources.  

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