Here in this post, I am going to tell you about the Open Science (OS) course which I have passed recently and to describe my opinion:
This course was undoubtedly a ticket for me to get to the plane of Open Science! It helped me to develop my new paradigm of research and innovation as a Ph.D. student. I learned that OS is not only about making our publications available and reusable via open access but also making our research data open by following these principles: findable, accessible, interoperable, and reusable. During this course, I learned the basics of open science, concepts, policies, boundaries, and requirements.
Open science, in general, aims to facilitate access to scientific content and encourage its reuse. It helps us share our work with other researchers in our field to build something bigger and better. Moreover, it can be constructive to access reliable and credible data, and while many published scientific findings might not be reliable.
In my opinion, one of the main reasons that the widespread adoption of open practices has not yet been achieved is that researchers are uncertain about how sharing their work will affect their careers. But, during this course, I comprehended that researchers could use open practices to their advantage to gain more citations, media attention, potential collaborators, job opportunities, and funding opportunities so that they can update their research cycle.
One of the most valuable parts of this course was being introduced to and getting familiar with the infrastructures, tools, and platforms to work in an open environment, i.e., the wide range of tools and platforms that are available and developing in order to help researchers in different stages of their scientific life such as research, analysis, writing, publications, outreach, and assessment. Among all, access to the very local environment, which is now available in many different scientific societies and universities, is of the most interest. For example, the university has recently started to help students and faculty to practice open science by developing a service called Unios.
As a Ph.D. student and researcher in the field of Machine learning in Fluid Dynamics, I normally deal with very new approaches, and methodologies, which are developed or being upgraded by a very limited yet outspread scientific society, and their rate of progress is relatively high. So, the size of the community, together with the rate of model development in this field, has led this society to move towards Open science to some extent. For example, most of the recent works has been published as preprints on open access platforms, and more importantly, the codes and datasets which are the heart of the research, are partially available on GitHub. But despite this, I had not questioned myself whether the way I am doing research was also aligned with those principles or not until I participated in this course at UC3M. And throughout the course, I understood why this way helps my research community and I am now clear about the way I want to do research using Open Science and to change the future practice of my research.
Moreover, before this course, I could not describe why it is good or beneficial to be an open scientist, and I was unaware of some of the traditional practices that are considered as “not open.” but now I can fully identify and appreciate what and how they do science and I plan to follow these principles during my PhD and throughout my career. Thanks to the informative presentations and support of the brilliant organizing team of this course, the way to become an open scientist is now more transparent and more achievable for me. If I want to anticipate my plans to become an “Open Scientist” during my Ph.D., some of the steps can be: Storing my data using a perennial system or format in compliance with my team or university policy, submitting my publications to open access journals, deposit my publications in an open archive, taking part in discussions within my disciplinary community about pre-publications deposited in the open archive, sharing research data and source code that I developed, following the evolutions of open science and get involved. Accordingly, I will be the ambassador of Open Science in my research group and department.