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Difficulty level
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This lecture focuses on where and how Jupyter notebooks can be used most effectively for education.
Difficulty level: Beginner
Duration: 34:53
Speaker: : Thomas Kluyver
Course:
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 lesson introduces the practical usage of The Virtual Brain (TVB) in its graphical user interface and via python scripts. In the graphical user interface, you are guided through its data repository, simulator, phase plane exploration tool, connectivity editor, stimulus generator, and the provided analyses. The implemented iPython notebooks of TVB are presented, and since they are public, can be used for further exploration of TVB.
Difficulty level: Beginner
Duration: 1:12:24
Speaker: : Paul Triebkorn
This tutorial covers the fundamentals of collaborating with Git and GitHub.
Difficulty level: Intermediate
Duration: 2:15:50
Speaker: : Elizabeth DuPre
This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.
Difficulty level: Beginner
Duration: 1:16:04
Speaker: : Erin Dickie and Sejal Patel
This lesson describes how DataLad allows you to track and mange both your data and analysis code, thereby facilitating reliable, reproducible, and shareable research.
Difficulty level: Intermediate
Duration: 59:34
Speaker: : Yaroslav O. Halchenko
This video gives a short introduction to the EBRAINS data sharing platform, why it was developed, and how it contributes to open data sharing.
Difficulty level: Beginner
Duration: 17:32
Speaker: : Ida Aasebø
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
Speaker: : Maaike van Swieten
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
This video demonstrates how to find, access, and download data on EBRAINS.
Difficulty level: Beginner
Duration: 14:27
Speaker: : Maaike van Swieten
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