Advice for 2022 OSB/NWB GSoC applicants
Background reading
Read the Open Source Brain paper as well as the recent Neurodata Without Borders paper. Note the OSB paper only briefly discusses extensions for NWB; OSB is undergoing a major expansion (v2.0) to allow sharing of data as well as models in neuroscience. The beta site for sharing NWB files on OSB is here: http://v2.opensourcebrain.org and a standalone instance of the NWB Explorer (accessible without logging in) can be found here: http://nwbexplorer.opensourcebrain.org.
Suggested activities prior to application
Sign up to GitHub if you’re not already there.
Create an OSB v2 user account & link your GitHub account to it.
Have a look at the example converted data sets which have been put online here: http://nwbexplorer.opensourcebrain.org.
There are scripts for converting different data formats (e.g. Matlab, IgorPro) to NWB format here .
Install pynwb and get some of the above scripts/notebooks working locally.
Make a minor update to the existing scripts (or just README) to improve these existing examples.
There is also a list of potentially interesting datasets which could be converted to NWB here: Issues · OpenSourceBrain/NWBShowcase · GitHub.
Some datasets which were converted during previous years’ GSoC project were:
- 2020: Ferguson et al. 2015 and Lantyer et al. 2018 .
- 2021: GSoC_2021_OSB_NWB, WormsenseLab_ASH.
Find some other public datasets (e.g. single cell electrophysiology recordings, population (calcium) imaging, behavioural studies) which you think would be appropriate for conversion to NWB format, to list with your application. Focus on datasets that are well described/structured/annotated, but in a non-NWB format (to minimise need to involve original data producers)! Also open issues as outlined above with links to the data.
Note 1: There are an increasing number of NWB compatible datasets available on the DANDI Archive. For this reason, there is a pressing need to test and ensure these are compatible with our NWB Explorer, rather than make new datasets which will be compatible with it from the start. Applicants who would be prepared to work to test the NWBE interface and make updates for compatibility with other independently developed datasets (e.g. as last year’s applicant did) would be very welcome!
Note 2: Please share the draft of your application early to allow feedback before the application deadline!
Essential information to include in your application:
- The list of potential datasets to convert as discussed above
- Details on the course currently being followed and a link to the course webpage.
- What are your time commitments during the coding period? Please be specific about this, work/exam commitments etc. Are you planning any vacations this summer? How many classes are you taking this summer?
- How many hours per week will you be able to spend on this project?
- If you have any evidence of your coding abilities (e.g. contributions to open-source projects) and/or background in neuroscience, please let us know about it. Send links to specific public repositories showing commits by you.
- Details of any previous experience in data analysis or computational modelling.