The Data-Sharing Problem in Neuroscience

Systems neuroscience is facing an enormous problem. New technologies for recording neural activity are generating huge volumes of data, which are rapidly becoming too large for any one lab to make sense of. But as datasets get larger and richer, they also become more difficult to share, analyze and store. Neuroscience, particularly neurophysiology, has lagged behind other fields in developing an infrastructure for easily sharing data, but the potential benefits are enormous. The MP3, a standardized format for encoding audio files, revolutionized the music industry. Large-scale efforts in other fields, such as the Sloan Digital Sky Survey in astronomy and the Human Genome Project and follow-on efforts in genomics, transformed those fields. In this series, we explore the challenges the field faces in developing a widespread data-sharing infrastructure and some of the solutions that are in the works and offer examples of specific projects that are implementing these tools.

Part 1: Why Neurophysiology Needs an MP3

When it comes to data sharing, neuroscience lags behind many other fields. But a growing number of large-scale projects are inspiring new efforts to develop workable tools.

Part 2: Taming the Wild Data World of Neuroscience

Driven by the growing number of large-scale collaborations, researchers are developing new ways to standardize both data and analysis pipelines.

Part 3: How BrainCogs Learned to Share: A Case Study

Members of the multi-lab BrainCogs collaboration are using DataJoint to more easily access each other’s data.

Part 4: Standardizing Data Across Species: A Case Study

A multilab collaboration at the University of Washington is developing ways to compare data from humans and monkeys.