This talk describes the NIH-funded SPARC Data Structure, and how this project navigates ontology development while keeping in mind the FAIR science principles. 

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. 

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

This lecture covers structured data, databases, federating neuroscience-relevant databases, and ontologies. 

This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.

This lecture focuses on ontologies for clinical neurosciences.

This lesson gives a description of the BrainHealth Databank, a repository of many types of health-related data, whose aim is to accelerate research, improve care, and to help better understand and diagnose mental illness, as well as develop new treatments and prevention strategies. 

This lesson corresponds to slides 46-78 of the PDF below. 

This lesson describes not only the need for precision medicine, but also the current state of the methods, pharmacogenetic approaches, utility and implementation of such care today.

This lesson corresponds to slides 1-50 of the PowerPoint below. 

This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.

This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.

This lecture focuses on the structured validation process within computational neuroscience, including the tools, services, and methods involved in simulation and analysis.

This session provides users with an introduction to tools and resources that facilitate the implementation of FAIR in their research.

Maximize Your Research With Cloud Workspaces is a talk aimed at researchers who are looking for innovative ways to set up and execute their life science data analyses in a collaborative, extensible, open-source cloud environment. This panel discussion is brought to you by MetaCell and scientists from leading universities who share their experiences of advanced analysis and collaborative learning through the Cloud.

This brief video provides an introduction to the third session of INCF's Neuroinformatics Assembly 2023, focusing on how to streamling cross-platform data integration in a neuroscientific context. 

This talk describes the challenges to sustained operability and success of consortia, why many of these groups flounder after just a few years, and what steps can be taken to mitigate such outcomes. 

This talk discusses the BRAIN Initiative Cell Atlas Network (BICAN), taking a look specifically at how this network approaches the design, development, and maintenance of specimen and sequencing library portals. 

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. 

This brief talk describes the challenge of global data sharing and governance, as well as efforts of the the Brain Research International Data Governance & Exchange (BRIDGE) to develop ready-made workflows to share data globally. 

This talk describes how to use DataLad for your data management and curation techniques  when dealing with animal datasets, which often contain several disparate types of data, including MRI, microscopy, histology, electrocorticography, and behavioral measurements. 

This brief talk covers an analysis technique for multi-band, multi-echo fMRI data, applying a denoising framework which can be used in an automated pipeline.