Embracing Open Science: What I learned so far
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When I first started the Ticket to Open Science course at UC3M, I had already been exposed to the Open Science concept and was familiar with some of its tools. After all, I’m working on a research project funded by the European Union that has to comply with several Open Science standards. I was familiar with the FAIR principles and the importance of a data management plan and platforms like Zenodo. Yet, this course offered so much more. It made me realize how much I still had to learn and introduced me to many platforms and tools essential for conducting and sharing research effectively.
The course emphasized the importance of transparency, accessibility, and collaboration not only when disseminating research but also throughout the research process (as a new researcher, I confess that I had been focusing more on the finish line rather than the entire research process). It highlighted that each researcher is responsible for embracing these changes. It also made me realize the substantial effort involved in adhering to open science principles throughout the research process. This is not to say that progress hasn’t been made. Indeed, there are many tools and platforms available to facilitate or at least assist researchers in their Open Science journey. From platforms that help create data management plans based on standard templates, such as Argos or the Spanish version from Consorcio Madroño, to open data platforms like the Open Science Framework (OSF) and collaborative tools like GitHub or Overleaf, there is a wealth of support available in the Open Science universe (you just need to know where to look).
Reflecting on the concept of Open Science, it’s challenging to understand why any researcher would oppose it. The idea of promoting open, transparent, and inclusive research that enhances the reproducibility and reliability of researchers’ work, fosters greater collaboration across disciplines, and contributes to a more inclusive and equitable scientific community seems aligned with why most people become researchers in the first place. Yet, Open Science is still met with suspicion by many academics. Some are concerned about intellectual property and potential misuse when sharing data or methodologies, while others are more focused on individual achievements and publishing in high-impact journals. On top of that, it is undeniable that Open Science practices are resource-intensive, requiring time, funding, and technical skills that many researchers still lack.
The main issue, however, seems to be the lack of incentives. The current academic system rarely acknowledges or rewards efforts to share data or engage in Open Science practices. Researchers who invest time and effort in making their work open often do so without formal recognition or career advancement benefits. While some steps have been taken to address this, we still have a long way to go. As a PhD student, I believe young researchers are under more pressure to adopt Open Science practices while their work is still mostly evaluated based on their paper outputs.
I know there are no easy answers here, but I can see that building an Open Science network, like the one Eva Mendes is attempting with this course, can provide support, resources, and collaborative opportunities that make adopting open practices more feasible for researchers. It also helps promote awareness, educating other researchers on the value of Open Science and the available tools, hopefully shifting the academic culture towards Open Science. From my part, what I can do is lead by example, incorporate Open Science practices in my research, and hopefully inspire others to follow suit. After all, I believe in Open Science principles, but I can’t deny that it would be nice to be rewarded for it too.