Surveying Open Science practices in the OHBM community: An interview with Dr. Tibor Auer
By Kirstie Whitaker
Open science means different things to different people. It includes open data, open source code, preprints, preregistrations, and open access publications. Getting started with open science practices can be overwhelming, and there is considerable variability in their adoption across the OHBM community. I sat down with Tibor Auer to learn about the survey he has developed to capture different attitudes towards open science practices in order to better support everyone in doing the best research they can.
Hi Tibor, let’s get started with an easy question: who are you?
I am a Research Fellow in MRI at the Department of Psychology, Royal Holloway University of London, where I facilitate neuroimaging by contributing to methods innovation, as well as training and education. Neurofeedback is one of my main research interests, as it offers the opportunity to follow neural development during the training process, thus satisfying interest in both theory and application. I received my PhD in clinical neuroscience and implemented various neuroimaging techniques in a clinical environment. Then, I focused on the implementation and the optimization of fMRI-based neurofeedback, and investigated assumptions and mechanisms underlying a neurofeedback training.
Why do you care about open science?
I am probably not the only person who has found a cool paper, and tried out its methods on my own data…. and fabulously failed! There are so many steps to reproducing a paper. If you are lucky you can find the corresponding author’s current e-mail address. They may bother to reply to your questions. The authors need to be able to locate the corresponding version of their workflow. It has to be documented well enough that you can decipher the code and adapt it to your data. Those are a lot of “ifs” and most of us aren’t that lucky. The process isn’t transparent.
Transparency, defined as unambiguous description of the data and the approaches, is not only beneficial to reproducibility but also to productivity in the first place. Automated pipelines, such as automatic analysis, allow quick exploration of the analysis space. Once you set up the workflow on pilot data, it can be applied on the real data right away. The pipeline’s documentation, based on standards such as the Neuroimaging Data Model, ensures the longevity of the project by making transitions smoother for current and future users.
What is this survey and what does it cover?
I am conducting this survey to investigate the knowledge and adoption of open research practices, including sharing of data and materials, study preregistration and related activities. It has been largely inspired by a recent survey in Cardiff. I want to know how people think about Open Science practices, their influence (positive or negative) and how the perception of Open Science might depend on experience with actual solutions and tools. Probably the most important aspect is what people see as the greatest barriers to the uptake of open research practices, and whether/how they can be ameliorated by (local and global) training and support. The awareness of challenges and solutions might vary across career levels, fields, and sectors (e.g. public and private), and I would like to be able to capture this variance, because we can only achieve change if we understand and resolve our differences.
Why did you want to create the survey?
Open Science is not just a (better) way to do science. One day, hopefully, we can omit the ‘open’, because all science will be done this way. Getting to that point cannot be an authoritarian process. It can only happen based on consensus and as a bottom-up initiative. We must understand what Open Science means for each of us, what encourages or discourages us to be engaged with it, what kind of support may be the most effective. The survey itself may raise awareness and give some hints and ideas by mentioning specific solutions in the questions.
Who do you hope will fill out the survey?
My guess is that many responses will be from methods experts who already appreciate the benefits of Open Science practices, but I would really like to also hear from the broader community of neuroimagers. Answers from people who do not use any Open Science practices are particularly valuable; especially if they tell us their reasons. It is important to know which aspects of Open Science have the biggest reach at the moment, and how they are perceived by a broad range of people in the OHBM community.
Early career researchers and senior scientists have different, sometimes even conflicting, priorities and motivations which may often explain the slow implementation of Open Science practices at an institutional level. Efficient resolution of these conflicts is possible only if we understand and harmonise the different incentives faced by these disparate groups.
How long will the survey be open for?
I have two stopping criteria for the survey: either we reach one thousand participants, or we get to 30 April 2019, whichever is earlier. I would like to receive responses from at least five hundred people but ideally one thousand!
I really appreciate the support of International Neuroinformatics Coordinating Facility (INCF) and OHBM in disseminating the survey to their members. It is important to note, however, that you do not have to be in either of these communities to respond. Everyone is welcome to submit their opinions.
What will you do with the results when you have them?
A summary of the results will be shared within the UK Network of Open Science Working Groups and other professional platforms, including the related Special Interest Groups of the OHBM and the INCF, to feed into the formulation and harmonisation of our Open Science strategy. The main aim of the survey is to capture different points of view, but I also hope it will prompt people to talk with each other, and think about and understand perceptions other than their own.
Every such survey has an educational angle, as well. For example, a recent survey on data management and sharing lets people know about several data handling approaches they might have not thought of before but they may try out after filling out the questionnaire. I hope this survey will encourage people to consider solutions unfamiliar to them and understand how they could benefit from additional tools.
Fantastic, I’m so looking forward to reading the results!
Thank you! Here’s the link again
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