This post is part of the series PhD Talk for AcademicTransfer: posts written for the Dutch academic career network AcademicTransfer, your go-to resource for all research positions in the Netherlands.
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I remember the first time I heard about publishing open access. I was a PhD candidate at that time, talking with my bestie who was also doing her PhD. In her research group, the focus was on publishing open access. When she first mentioned that it required her (or her research group) to pay to publish, I gave her a very puzzled look.
I may have even asked her in my ignorance if it’s the same as buying your diploma at an expensive private university. She continued to explain that open access changes the publishing model from the traditional subscription model, where the reader pays, to a model where the author pays so that everyone can read their work.
It took me a few more years before I really understood the value of open access publishing. I started to consciously look for open access journals, which were often newer and less known to me. After exploring the work published in these journals, I started to dip my toe in open access publishing and submitted an article. I had a positive experience, and have tried since then to send a bit over half of my work to open access journals, and see if I can publish my articles open access in the traditional subscription-based journals as well.
Many of you may have undergone a similar change in attitude over the past years. However, open access is just one part of the field of open science. I’d like to invite you today to think about the ways in which you can make your science more open, through the following concepts:
- open data: If you make your writing available through open access, it may also be good to make your dataset publicly available. Many open access journals even require you to make sure your data is in the public domain. If you make your data available online, think about applying as well the principles of FAIR data: findable, accessible, interoperable, and reusable
- open code: Which script did you use for processing your dataset to get to your results? Have you considered uploading the script in an online repository as well? Similar recommendations hold true for open code as for open data.
- open source software: A step further than sharing the script you used, would be to switch to the use of open source software and to share your improvements to the code with other users. Personally, I still struggle with this step, as I’m deeply rooted in commercial software that I’ve been using for a long time – but I’m keeping my eyes open to make the switch in the future.
- open collaborations: When research networks open up their projects, they can release a call for contributors. Often, open collaboration, with a free sharing of data and ideas among all those involved, regardless of their position and rank, is seen as the very ideal of open science.
- open peer review: Most traditional journals use blind or double-blind peer review. The identity of the reviewer is often unknown, and sometimes we truly wished we’d known the person who tore apart our work like that. Enter open peer review – a modality in which everyone’s identity is known. This approach is sometimes used by open access publishers, and you will find the name of the editor and the names of the reviewers on the paper, and in some cases the reports of the reviewers as well.
- preprints: Preprints are becoming more and more common. We submit a preprint as we work on a paper, or right at the moment that we submit our work to peer review. At that moment, our work is available to others, who can comment on it, while we wait for the outcome of the review process at the journal.
- preregistration of research: For research in the life sciences, preregistration of protocols, research questions etc is becoming more common, as it is seen as a way to counteract the malpractice of data mining. In my field, this approach is not common yet.
How do you make your science more open? Let me know in the comments below!