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This video explains what metadata is, why it is important, and how you can organize your metadata to increase the FAIRness of your data on EBRAINS.

Difficulty level: Beginner
Duration: 17:23
Speaker: : Ulrike Schlegel

This video introduces the importance of writing a Data Descriptor to accompany your dataset on EBRAINS. It gives concrete examples on what information to include and highlights how this makes your data more FAIR.

Difficulty level: Beginner
Duration: 9:48
Speaker: : Ingrid Reiten
Course:

KnowledgeSpace (KS) is a data discoverability portal and neuroscience encyclopedia that was developed to make it easier for the neuroscience community to find publicly available datasets that adhere to the FAIR Principles and to provide an integrated view of neuroscience concepts found in Wikipedia and NeuroLex linked with PubMed and 17 of the world's leading neuroscience repositories. In short, KS provides a single point of entry where reseaerchers can search for a neuroscience concept of interest and receive results that include: i. a description of the term found in Wikipedia/NeuroLex, ii. links to publicly available datasets related to the concept of interest, and iii. up-to-date references that support the concept of interests found in PubMed. APIs are available so that developers of other neuroscience research infrastructures can integrate KS components in their infrastructures. If your repository or your favorite repository is not indexed in KS, please contact us.

 

Difficulty level: Beginner
Duration: 6:14
Speaker: : Heather Topple

In this lesson, users will learn about the importance of proper citation of software resources and tools used in neuroscientific research. 

Difficulty level: Beginner
Duration: 58:00
Course:

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

 

Difficulty level: Beginner
Duration: 1:09:16
Speaker: : Aaron J. Newman

JupyterHub is a simple, highly extensible, multi-user system for managing per-user Jupyter Notebook servers, designed for research groups or classes. This lecture covers deploying JupyterHub on a single server, as well as deploying with Docker using GitHub for authentication.

Difficulty level: Beginner
Duration: 1:36:27
Speaker: : Thomas Kluyver

This demonstration walks through how to import your data into MATLAB.

Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®

This lesson provides instruction regarding the various factors one must consider when preprocessing data, preparing it for statistical exploration and analyses. 

Difficulty level: Beginner
Duration: 15:10
Speaker: : MATLAB®

This tutorial outlines, step by step, how to perform analysis by group and how to do change-point detection.

Difficulty level: Beginner
Duration: 2:49
Speaker: : MATLAB®

This tutorial walks through several common methods for visualizing your data in different ways depending on your data type.

Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®

This tutorial illustrates several ways to approach predictive modeling and machine learning with MATLAB.

Difficulty level: Beginner
Duration: 6:27
Speaker: : MATLAB®

This brief tutorial goes over how you can easily work with big data as you would with any size of data.

Difficulty level: Beginner
Duration: 3:55
Speaker: : MATLAB®

In this tutorial, you will learn how to deploy your models outside of your local MATLAB environment, enabling wider sharing and collaboration.

Difficulty level: Beginner
Duration: 3:52
Speaker: : MATLAB®

The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.

Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez

This lesson provides an overview of self-supervision as it relates to neural data tasks and the Mine Your Own vieW (MYOW) approach.

Difficulty level: Beginner
Duration: 25:50
Speaker: : Eva Dyer

This video introduces the key principles for data organization and explains how you could make your data FAIR for data sharing on EBRAINS.

Difficulty level: Beginner
Duration: 10:54
Course:

This lesson gives a quick walkthrough the Tidyverse, an "opinionated" collection of R packages designed for data science, including the use of readr, dplyr, tidyr, and ggplot2.

Difficulty level: Beginner
Duration: 1:01:39
Speaker: : Thomas Mock

This lesson provides a hands-on tutorial for generating simulated brain data within the EBRAINS ecosystem. 

Difficulty level: Beginner
Duration: 32:58
Speaker: : Jil Meier