Open science x academia: what’s working and what’s not
by Jessica Bou Nassar and Melina Papalampropoulou-Tsiridou, Science & Policy Exchange (SPE)
As two early career researchers (ECRs), we have been experiencing the power of open science firsthand through our work in academia as well as witnessing it from a distance as we observe researchers from all over the world come together, share science, and save lives, amidst a global pandemic. The idea of open access data and an academic community where collaboration and exchange are fostered has led major funding agencies like the National Institutes of Health (NIH) to commence multiple relevant initiatives. In 2017, 12 recipients received an NIH 9 million dollar grant to create an open source, cloud-based biomedical data directory. Such initiatives demonstrate the importance of data sharing to advance technology transfer and improve the quality of human lives and patients suffering from debilitating conditions at a faster pace. Open-source data have also assisted in the fight against COVID-19. A more recent open-access initiative by the NIH provides a detailed database of computational resources developed from various organizations including federal agencies, public consortia, and private entities. As of January 2023, the NIH will request that all its funded researchers submit a detailed plan demonstrating how their scientific data will be managed and shared.
The Canadian Institutes of Health Research (CIHR) recognizes the importance of open science and has created an action plan and several initiatives promoting open data and sharing. Similarly, the Allen Brain institute, one of the biggest not-for-profit research institutes, has introduced the Neurodata without Borders project aiming to establish universal guidelines to share, archive, use, and build analysis tools for neurophysiology data.
As ECRs and academics, we are excited about these initiatives (and similar ones). However, multiple barriers within academia that could hinder the advancement of open science should be addressed:
1. The dominant definition of research excellence is not aligned with open science values.
The current ‘definition’ of research excellence is engrained in academic culture and has been shaped by criteria that encourage the “productization of science”. This includes metrics such as impact factors and h-indices to assess research. Under existing conditions, efforts made by researchers towards open science are seen as “additional burdens without rewards”. Imagine being an ECR who has spent time curating an open access database only to receive zero credit. Utrecht University is changing the status quo by adopting new evaluation criteria for recruitment and promotion, which include engagement in teamwork and efforts to advance open science. Additionally, it is dismissing traditional evaluation criteria such as impact factors and h-indices.
Funding agencies define the requirements that allow researchers to benefit from funds and thus shape research excellence. Grant applications are generally assessed using 15 criteria, of which none are related to open science. Funding agencies could help promote open science by modifying the evaluation criteria to align with it. The next time you apply for a grant, would you like your contributions to the public and collaborations with different researchers to be considered in the assessment? Share your thoughts in the comment section below!
2. ECRs and academics might not have the skills to engage in open science solutions.
In a panel discussion co-hosted by Science & Policy Exchange, panelists discussed how the lack of familiarity with open science and platforms to share research and data has been a barrier to synergizing researchers’ efforts. This calls for training programs that focus on open science initiatives and equip researchers and scientists with the necessary skills to engage in it. The Department of Psychology at the Ludwig-Maximilians-University Munich mandates training on reproducible science which includes classes on study preregistration and open access data (find out more about these and other open science solutions here).
3. A competitive mindset in academia could hinder open science.
A balance between competition and collaboration should be struck within and across research labs. Competition might incentivize researchers, but unhealthy competition can be toxic to lab cultures and hinder the progression of science. A competitive mindset could drive researchers to be possessive of their datasets and prevent them from sharing their research. In contrast, open science is based on collaboration, openness, and sharing. Therefore, fostering collaborations is key to its advancement. This requires a cultural shift within academia, which could be promoted by changing incentive values, rethinking research excellence, and providing training on effective collaboration.
We are both excited to see a shift within academia towards the advancement of open science, since we like to engage the public in our research! Did you know that open science initiatives might spark the public interest in academic work? In 2017 a neuroscientific game was launched as a collaboration between the University of Washington and Allen Brain Institute that enabled citizens with a science background to trace neuronal structures, allowing 3D reconstructions of neurons. Therefore, open science is not only the door of science to collaboration, but also that to engagement and outreach. Will you fully embrace it?