With the advent of the brain Initiatives in the US and other countries, the scale and diversity of neuroscience data continues to grow. DANDI (https://dandiarchive.org/) is a US BRAIN Initiative supported data archive and collaboration platform that is housed using several cloud services. The intent of the archive is to make data accessible to others, but also to transform the way people think about computing and data in labs. The platform provides access to cellular timeseries and imaging data that ranges from MBs to TBs per file, and growing. This diversity challenges all of us to rethink where and how we should store and compute data. In this talk, I will briefly cover the infrastructural components, the use of different cloud resources, and the technical developments needed to standardize data for search, and computation, and to provide easy access to pieces of data. I will also present a set of social and technical challenges that will need to be tackled by the neuroscience community and other disciplines as the field evolves to co-design and generate scientific output around the planet.

Author Bio:

Satrajit Ghosh is a Principal Research Scientist at the McGovern Institute for Brain Research at MIT and an Assistant Professor of Otolaryngology at Harvard Medical School. He directs the Senseable Intelligence Group whose research portfolio comprises projects on spoken communication, brain imaging, and informatics to address gaps in scientific knowledge in three areas: the neural basis and translational applications of human spoken communication, machine learning approaches to precision psychiatry and medicine, and preserving information for reproducible research.

For further information:

RRoCCET21 is a conference that was held virtually by CloudBank from August 10th through 12th, 2021. Its intention is to inspire you to consider utilizing the cloud in your research, by way of sharing the success stories of others. We hope the proceedings, of which this case study is a part, give you an idea of what is possible and act as a “recipe book” for mapping powerful computational resources onto your own field of inquiry.