EBRAINS Infrastructure Training
2nd Elephant User Workshop
Accelerate Structured and Reproducible Data Analysis in Electrophysiology
17-19 November 2020 | Virtual Event
Helpful Phython tutorials:
This event delves into challenges in the reproducibility of neuroscience workflows dealing with classical electrophysiological activity data, such as spiking data or local field potentials, from experiment or simulation.
The training will cover the complete cycle from generating structured and consistent data and metadata, accessing the data, pre-processing, setting up analysis workflows, up to the tracking of the provenance of the analysis results. In this context, the e-infrastructure services of EBRAINS offer a mature data, software and compute services ecosystem with community-driven tools developed in the framework of the Human Brain Project. In the first part of the workshop, participants will be trained in the use of tools covering the following topics:
- reading and manipulating electrophysiology data in Python using Neo 
- analysis of such data using Elephant 
- best practices for integrating metadata into your workflow to aid the analysis process
- best practices for structuring analysis results
- tracking data analysis pipelines using the HBP Knowledge Graph 
- collaboration and sharing documents using the HBP Collaboratory 
In the second part of the workshop, participants will work together with a tutor in small groups, on their own data and on particular personal interests in the scope of the workshop. To this end, participants are asked to provide a small abstract describing the data set they would like to bring and work on (contents of the dataset, data format, data size...) and the topic they are interested in. The latter may, for example, be related to: annotating the dataset with metadata for collaboration and sharing, working with the dataset in the Neo framework, or performing a certain kind of analysis with the data set. The goal of each group is to get started addressing the topic, identify solutions together with the tutors, and implement a first prototype of the required functionality.