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This lesson discusses the topic of credit and contribution in open and FAIR neuroscience, looking through the respective lenses of systems, teams, and people. 

Difficulty level: Beginner
Duration: 24:34
Speaker: : Tanya Brown

In this talk, you will hear about the challenges and costs of being FAIR in the many scientific fields, as well as opportunities to transform the ecology of the academic crediting system. 

Difficulty level: Beginner
Duration: 14:56
Speaker: : Zefan Zheng

This brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers. 

Difficulty level: Beginner
Duration: 7:10

In this lightning talk, you will learn about BrainGlobe, an initiative which exists to facilitate the development of interoperable Python-based tools for computational neuroanatomy.

Difficulty level: Beginner
Duration: 3:33

This is the third and final lecture of this course on neuroinformatics infrastructure for handling sensitive data. 

Difficulty level: Beginner
Duration: 1:11:22
Speaker: : Michael Schirner

In this lecture, you will learn about virtual research environments (VREs) and their technical limitations, (i.e., a computing platform and the software stack behind it) and the security measures which should be considered during implementation. 

Difficulty level: Beginner
Duration: 1:06:50
Speaker: : Marc Sacks

This lesson consists of a panel discussion, wrapping up the INCF Neuroinformatics Assembly 2023 workshop Research Workflows for Collaborative Neuroscience

Difficulty level: Beginner
Duration: 25:33
Speaker: :

This brief talk outlines the obstacles and opportunities involved in striving for more open and reproducible publishing, highlighting the need for investment in the technical and governance sectors of FAIR data and software. 

Difficulty level: Beginner
Duration: 8:38

This talk gives an overview of the complicated nature of sharing of neuroscientific data in an environment of numerous and often conflicting legal systems around the world. 

Difficulty level: Beginner
Duration: 14:00
Speaker: : Franco Pestilli

This talk provides an overview of the FAIR-aligned efforts of MATLAB and MathWorks, from the technological building blocks to the open science coordination involved in facilitating greater transparency and efficiency in neuroscience and neuroinformatics. 

Difficulty level: Beginner
Duration: 15:41
Speaker: : Vijay Iyer

This brief video provides a welcome and short introduction to the outline of the INCF Short Course in Neuroinformatics, held Seattle, Washington in October 2023, in coordination with the West Big Data Hub and the University of Washington. 

Difficulty level: Beginner
Duration: 4:58
Speaker: : Ariel Rokem

This opening lecture from INCF's Short Course in Neuroinformatics provides an overview of the field of neuroinformatics itself, as well as laying out an argument for the necessity for developing more sophisticated approaches towards FAIR data management principles in neuroscience. 

Difficulty level: Beginner
Duration: 1:19:14
Speaker: : Maryann Martone

This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology. 

Difficulty level: Intermediate
Duration: 33:41

This lesson continues from part one of the lecture Ontologies, Databases, and Standards, diving deeper into a description of ontologies and knowledg graphs. 

Difficulty level: Intermediate
Duration: 50:18
Speaker: : Jeff Grethe

This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects. 

Difficulty level: Beginner
Duration: 59:21
Speaker: : Alla Borisyuk

This lecture covers a wide range of aspects regarding neuroinformatics and data governance, describing both their historical developments and current trajectories. Particular tools, platforms, and standards to make your research more FAIR are also discussed.

Difficulty level: Beginner
Duration: 54:58
Speaker: : Franco Pestilli

This lesson gives an in-depth description of scientific workflows, from study inception and planning to dissemination of results. 

Difficulty level: Beginner
Duration: 44:41

Introduction of the Foundations of Machine Learning in Python course - Day 01.

High-Performance Computing and Analytics Lab, University of Bonn

Difficulty level: Beginner
Duration: 35:24
Speaker: : Elena Trunz

Optimization for machine learning - Day 02 lecture of the Foundations of Machine Learning in Python course.

High-Performance Computing and Analytics Lab, University of Bonn

Difficulty level: Advanced
Duration: 34:52
Speaker: : Moritz Wolter