  The BigScience Workshop was a value-driven initiative that spanned one and
half years of interdisciplinary research and culminated in the creation of
ROOTS, a 1.6TB multilingual dataset that was used to train BLOOM, one of the
largest multilingual language models to date. In addition to the technical
outcomes and artifacts, the workshop fostered multidisciplinary collaborations
around large models, datasets, and their analysis. This in turn led to a wide
range of research publications spanning topics from ethics to law, data
governance, modeling choices and distributed training. This paper focuses on
the collaborative research aspects of BigScience and takes a step back to look
at the challenges of large-scale participatory research, with respect to
participant diversity and the tasks required to successfully carry out such a
project. Our main goal is to share the lessons we learned from this experience,
what we could have done better and what we did well. We show how the impact of
such a social approach to scientific research goes well beyond the technical
artifacts that were the basis of its inception.
