NWB Workshops and Hackathons

Write full project title here

Key Investigators

Ryan Ly Ben Dichter

Project Description

Users described a large learning curve for understanding the NWB format and using the APIs. Although the tutorials were helpful in describing the steps to get started using NWB, they did not always explain the “why,” leaving some users frustrated at the complexity and difficulty of using NWB for their particular use case. Users also mentioned how if they are having difficulty learning how to work with NWB, the average researcher in their labs would have even more difficulty. Thus, I looked into creating a more beginner-friendly, interactive tutorial/mini-course on NWB, starting with PyNWB.

Objectives

Use open-source tools to build a beginner-friendly, interactive tutorial/mini-course on PyNWB.

Approach and Plan

Use the Binder-linked course framework here: https://github.com/ines/spacy-course

Progress and Next Steps

I started this project a while ago but made much more progress on it during this hackathon. It is now public on the NeurodataWithoutBorders GitHub organization: https://github.com/NeurodataWithoutBorders/pynwb-course

I have written most of Chapter 1 which deals with creating an NWB file object, adding TimeSeries data to it, and writing the object to disk.

The source code can be found here: https://github.com/NeurodataWithoutBorders/pynwb-course

And a live demo of the course can be found here: https://pynwb-course.netlify.com/