This talk enumerates the challenges regarding data accessibility and reusability inherent in the current scientific publication system, and discusses novel approaches to these challenges, such as the EBRAINS Live Papers platform. 

This brief video gives an introduction to the eighth session of INCF's Neuroinformatics Assembly 2023, focusing on FAIR data and the role of academic journals. 

This talk gives an overview of the perspectives and FAIR-aligned policies of the academic journal Public Library of Science, better known as PLOS. This journal is a nonprofit, open access publisher empowering researchers to accelerate progress in science. 

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

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 presentation by the OHBM OpenScienceSIG covers common scenarios where Git can be extremely valuable. The essentials covered include cloning a repository and keeping it up to date, how to create and use your own repository, and how to contribute to other projects via forking and pull requests.

DataLad is a versatile data management and data publication multi-tool. In this session, you can learn the basic concepts and commands for version control and reproducible data analysis. You’ll get to see, create, and install DataLad datasets of many shapes and sizes, master local version workflows and provenance-captured analysis-execution, and you will get ideas for your next data analysis project.