At first glance, it may seem obvious to associate Open Source and Open Science, whose synergies seem natural. Open Science is the unhindered dissemination of research publications and data. Open Source can be seen here as one of the branches of Open Science in the same way as Open Access or Open Research Data.
Open Source, which defends the freedom of access to and modification of software, therefore appears to be a perfectly complementary approach, both in terms of providing the tools and platforms for Open Science and in terms of the transparency and openness of results to the community. There are many remarkable examples of this with initiatives such as GitHub and, historically, Mozilla Science Lab.
But a more nuanced view, informed by the experience of these projects, particularly in business and public/private relations, shows us that there are obstacles. Cultural differences, intellectual property issues (with a wide variety of licences) and the challenges of funding and commercialising projects all come to the fore.
The need for companies to achieve a return on their investment can lead to constraints on intellectual property - or even patentability - that conflict with Open Science. Similarly, laboratories are increasingly seeking to add value to their work and collaborations in order to consolidate their budgets, which are not always sufficient. These constraints can call into question the Open Source nature of tools and results.
So we see that challenges remain, including in the management of open data and compliance with publication standards. Overcoming these cultural, legal or financial obstacles in Open Science projects requires a good understanding of the issues at stake for all the partners and the adjustments that need to be made. But this is the only way to build sustainable opportunities and real leadership for the Open Source and Open Science ecosystem in research.
By way of illustration, OpenStudio will be focusing in particular on the field of AI and its European challenges, drawing in particular on the experience of the Atlas of Productive Synergies, LongRun and Mellia, research and scientific cooperation projects (four CIFRE theses are currently in progress as part of public/private collaborations).