Since its launch in 2013, BIDS has been dedicated to accelerating data-driven discovery by fostering an environment of open inquiry and cross-disciplinary collaboration. We have successfully broken down traditional academic silos, uniting domain experts from the life, physical, and social sciences, as well as the arts and humanities, with methodological leaders in computer science, statistics, and applied mathematics.
BIDS is expertly positioned as the central hub for advancing interdisciplinary data science research, academic training, and software development within the UC Berkeley College of Computing, Data Science, and Society. BIDS houses UC Berkeley's Open Source Program Office and champions open science, open source software, and open scholarship. We serve as a discipline-agnostic space to rally Berkeley's unique ecosystem, driving forward innovative collaborations that explore the profound impacts of Artificial Intelligence on both science and society.
UC Berkeley and UCSF have launched a joint program called the Bakar Computational Biomedicine Initiative to develop the frontier of AI and biomedicine, tremendously accelerating advances in clinical care. The new partnership brings together world-class faculty expertise in computing, AI, statistics, biology, and medicine, to speed discovery in everything from disease prevention, to early detection and new therapeutics in healthcare.
As part of this effort, at BIDS our team of open source research software engineers (OS-RSEs), product managers, and computational postdoctoral researchers will build the BioJupyter platform. Based on the widely adopted architecture of Project Jupyter and developed as part of the existing Jupyter ecosystem, with advancements and contributions to existing Jupyter components as well as the development of new tools, BioJupyter will bring next-generation features to facilitate collaboration in data-intensive, AI-powered biomedical research. These will include, but not be limited to, advances in core Jupyter components for collaboration and data sharing across deployments in separate hosting environments (ranging from local clusters and HPC facilities to the cloud), integration of AI agents and tools into the research workflow, sharing of intermediate results, code and pre-publication outputs with fine-grained access control, and fluid integration of these Jupyter deployments alongside existing research tools and environments that are independent of Jupyter.
OS-RSEs bring software engineering expertise and open source development practices to interdisciplinary projects. They play the role of an "expert collaborator" who solves problems at the intersection of research, software, and modern computing infrastructure. They regularly investigate -- and propose solutions to -- open-ended, unstructured challenges that arise from the computational needs of researchers. They scope, and deliver on technical requirements that require an in-depth evaluation of cutting-edge data science and AI applications. They are integral members of a diverse team, co-creating the BioJupyter platform to solve real-world challenges in the biomedical sciences.
OS-RSEs work closely with senior researchers, industry partners, and stakeholders across global scientific open source projects in the Jupyter ecosystem, as well as those of the computational tools used by our researchers today, including Scientific Python, R, and beyond. They create, improve, and maintain parts of the open source software ecosystem that underpins global innovation in data science and AI. They advocate for open science and open scholarship best practices, and meet national and global standards around responsible and ethical uses of technology. They showcase research outputs and software tools to the research community and industry partners through presentations, research papers, blog posts, interactive data visualizations, and open source software packages.