  Neuroscientists are now able to acquire data at staggering rates across
spatiotemporal scales. However, our ability to capitalize on existing datasets,
tools, and intellectual capacities is hampered by technical challenges. The key
barriers to accelerating scientific discovery correspond to the FAIR data
principles: findability, global access to data, software interoperability, and
reproducibility/re-usability. We conducted a hackathon dedicated to making
strides in those steps. This manuscript is a technical report summarizing these
achievements, and we hope serves as an example of the effectiveness of focused,
deliberate hackathons towards the advancement of our quickly-evolving field.
