More and more of the experimental datasets behind publications in neuroscience are being publicly released, increasing transparency of the scientific process and allowing reuse of the data for new investigations. However, these datasets, which can include electrophysiology, 2D/3D imaging data and behavioural recordings, are not always in an accessible format, and it may take some effort for researchers to access and analyse the data before deciding to use it in their own research. The Neurodata Without Borders (NWB, https://www.nwb.org) initiative is developing a format for sharing data from neurophysiology experiments which, together with APIs for handling files in the format, promises to greatly facilitate the sharing and reuse of data in neuroscience.
This project will involve converting a number of publicly available datasets to NWB format, adding structured metadata to ensure maximal understandability and reusability of the data. The converted datasets will be made available through the new NWB Explorer on the Open Source Brain repository (http://nwbexplorer.opensourcebrain.org) which allows visualisation of the data as well as interactive analysis through an inbuilt Jupyter notebook.
Skills required: Python; open source development; neuroscience (experimental or computational) background; data analysis.
Select a number of publicly available datasets which require conversion to NWB format (see here for examples).
Read, understand and appreciate original publications related to data, convert datasets to NWB format, adding annotations and metadata to facilitate interpretability & reuse of the data by others. Document process to aid others.
Make data available via the NWB Explorer on the Open Source Brain repository
Tags: OSB, NWB, Python, HDF5, data analysis, open access.