This is the second of three lectures around current challenges and opportunities facing neuroinformatic infrastructure for handling sensitive data. 

This lesson provides an overview of how to conceptualize, design, implement, and maintain neuroscientific pipelines in via the cloud-based computational reproducibility platform Code Ocean. 

This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.

This hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines. 

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. 

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

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. 

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. 

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.

This brief video provides an introduction to brainlife.io, a free cloud computing platform for neuroimaging data analysis. 

This video will document the process of uploading data into a brainlife project using ezBIDS.

This lesson provides a brief visual walkthrough on the necessary steps when copying data from one brainlife project to another. 

This brief video walks you through the steps necessary when creating a project on brainlife.io. 

This lesson describes and shows four different ways one may upload their data to brainlife.io.

This quick video presents some of the various visualizers available on brainlife.io

This brief video rus through how to make an accout on brainlife.io.

This talk highlights a set of platform technologies, software, and data collections that close and shorten the feedback cycle in research. 

This tutorial provides instruction on how to simulate brain tumors with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls.