Toward Community-Driven Big Open Brain Science: Open Big Data and Tools for Structure, Function, and Genetics

As acquiring bigger data becomes easier in experimental brain science, com-putational and statistical brain science must achieve similar advances to fullycapitalize on these data. Tackling these problems will benefit from a moreexplicit and concerted effort to work together. Specifically, brain sciencecan be further democratized by harnessing the power of community-driven tools, which both are built by and benefit from many different people with different backgroundsand expertise. This perspective can be applied across modalities and scales and enables collabora-tions across previously siloed communities.

A. S. Charles, B. Falk, N. Turner, T. D. Pereira, D. Tward, B. D. Pedigo, J. Chung, R. Burns, S. S. Ghosh, J. M. Kebschull, and others, in Annual Review of Neuroscience.
A community-developed open-source computational ecosystem for big neuro data

A series of open source and web accessible resources for studying neuroscience related data.

J. Vogelstein, E. Perlman, B. Falk, A. Baden, W. G. Roncal, V. Chandreshekhar, F. Collman, S. Seshamani, J. Patsolic, K. Lillaney, M. Kazhdan, R. J. Hider, D. Pryor, J. Matelsky, A. Crow, M. Write, S. Smith, T. Gion, P. Manavalan, B. Wester, M. Chevillet, E. Trautman, K. Khairy, E. Bridgeford, D. Kleissas, D. J. Tward, M. Miller, R. Vogelstein, K. Deisseroth, and R. Burns, in Nature methods.