This lightning talk gives an outline of the DataLad ecosystem for large-scale collaborations, and how DataLad addresses challenges that may arise in such research cooperations.

This talk gives a brief overview of current efforts to collect and share the Brain Reference Architecture (BRA) data involved in the construction of a whole-brain architecture that assigns functions to major brain organs. 

This lesson is the first part of a three-part series on the development of neuroinformatic infrastructure to ensure compliance with European data privacy standards and laws. 

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

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. 

This lesson gives a quick introduction to the rest of this course, Research Workflows for Collaborative Neuroscience. 

In this workshop talk, you will receive a tour of the Code Ocean ScienceOps Platform, a centralized cloud workspace for all teams. 

This talk describes approaches to maintaining integrated workflows and data management schema, taking advantage of the many open source, collaborative platforms already existing.

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

This lesson provides an introduction to the DataLad, a free and open source distributed data management system that keeps track of your data, creates structure, ensures reproducibility, supports collaboration, and integrates with widely used data infrastructure.

This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments. 

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

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. 

This talk describes the challenges in sharing personal, and in particular, health data, such as data anonymization and maintaining GDPR compliance. 

This lecture provides a detailed description of how to incorporate HED annotation into your neuroimaging data pipeline. 

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. 

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. 

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

In this lesson, you will learn how to understand data management plans and why data sharing is important. 

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.