OpenNeuro meeting summary
A few weeks ago (October 15th, 2018) we hosted a meeting at Stanford University to affirm the goals and further advancements of OpenNeuro. We invited our engineering team (Squishymedia), the NIMH data science and sharing team as well as a representative of NIMH extramural funding division. The goal of this meeting was for all participants to understand the future aims, aspirations, and challenges of extending the OpenNeuro repository.
The meeting was organized to have introductions and overview talks in the morning, then hold planning discussions in the afternoon. We began by providing a history and mission of OpenNeuro. Our mission is to promote data sharing, reusability, and transparency within the brain sciences field. An important feature of OpenNeuro is the automatic validation performed using our BIDS validator before the user can complete their dataset upload onto the repository. This ensures that all datasets on OpenNeuro are BIDS compliant. The main objectives are to provide a robust repository for researchers to share their data, allow for easy and streamlined querying of all the data available on OpenNeuro, and provide support for analyzing data directly on OpenNeuro. In the afternoon we discussed outstanding issues and future enhancements for OpenNeuro. These were evaluated by how each proposal may improve user functionality and ranked by importance. We established a clear path moving forward for enhancing reliability and ease of use for the end user.
We understand that OpenNeuro cannot be the most effective repository without getting community input on features that you may see are useful to your work. We have opened a user suggestions forum. This forum is public and recommendations can be voted upon by the community.
Looking forward, we plan on continuing to expand OpenNeuro to further help the community share their data, reuse other researchers data, run analysis directly within the repository, and expand into other modalities (i.e. PET imaging). We are continuously planning and preparing for how we can scale efficiently and stay sustainable as we grow. We are prepared to provide a robust repository for the future of data sharing, reusability, and transparency within the brain imaging sciences.
We would like to thank everyone for their time and participation in this meeting!