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Progress in biomedical research requires studying datasets much larger than previously thought. However, the data is not easy to find, and is curated and analysed locally, in redundant, often wasteful and opaque ways. The FAIR data principles provide a strategy for increasing openness in research, by making the outcomes of scientific research findable, accessible, interoperable and reproducible. But these principles are often not enough to solve the challenge of collaborative science: we need tools that will allow scientists to join forces and work together instead of in parallel, potentially not only among academic researchers but also including citizen scientists. The current working methodology makes it difficult to tackle this type of challenge, leading to duplication of effort and waste: for example, in brain imaging, it is not infrequent that 10 up to 50% of data is excluded from analysis, because of our inability to curate it; and when such lengthy processes are engaged, they are performed independently by each research team despite the data being public.
We are building a Web platform – the NeuroWebLab – to go beyond FAIR, and allow neuroscientists to collaborate concurrently on the same data, extending the real-time paradigm of tools such as Etherpad to different data modalities. During the last years we have gathered extensive experience building Web tools for real-time collaboration: Brainspell, BrainBox and MicroDraw. We build on this experience to develop a general Web platform for distributed scientific collaboration on open data, which will include the data modalities we are developing ourselves, and which could also be easily extended to new data modalities. Finally, we are building a portal – the BrainWeb – to allow researchers to discover collaborators and projects, providing tools for strengthening online participation and engagement.