The COVID-19 pandemic created unprecedented challenges, uncertainty, and destabilization for researchers. With labs and workspaces temporarily shut down due to the imposed lockdowns, scientists had to adapt to new conditions, including conducting scientific projects at home. Read this blog to discover how easy access to essential relevant research and open data sharing helped tackle the global public health emergency.
While the world closed, science opened
Researchers increasingly used their own data and data from others during COVID-19
The pandemic caused significant disruption to the scientific process leading to a swift change in perspective 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’.
More work needed
We 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 had been 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 ongoing challenges posed by COVID-19 and prepare for future global health emergencies.
Open data at F1000
F1000 data policies
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.
We endorse 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’.
The benefits of making your data open
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 to25% increase in citations for their articles.
Open data enables the reuse of data which was 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 shone a 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.
How do you share research data openly?
Learn all you need to know about making your data as open as possible and as closed as necessary.