In this talk, you will learn about the standardization schema for data formats among two of the US BRAIN Initiative networks: the Cell Census Network (BICCN) and the Cell Atlas Network (BICAN).
This lesson describes the current state of brain-computer interface (BCI) standards, including the present obstacles hindering the forward movement of BCI standardization as well as future steps aimed at solving this problem.
Brief introduction to Research Resource Identifiers (RRIDs), persistent and unique identifiers for referencing a research resource.
Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (e.g., antibodies, model organisms, and software projects) in biomedical literature to improve the transparency of research methods.
The Brain Imaging Data Structure (BIDS) is a standard prescribing a formal way to name and organize MRI data and metadata in a file system that simplifies communication and collaboration between users and enables easier data validation and software development through using consistent paths and naming for data files.
Neurodata Without Borders (NWB) is a data standard for neurophysiology that provides neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data.
The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication.
This lesson provides a brief introduction to the Neuroscience Information Exchange (NIX) Format data model, which allows storing fully annotated scientific datasets, i.e., data combined with rich metadata and their relations in a consistent, comprehensive format.
This lecture provides an overview of successful open-access projects aimed at describing complex neuroscientific models, and makes a case for expanded use of resources in support of reproducibility and validation of models against experimental data.
This lesson provides an overview of Neurodata Without Borders (NWB), an ecosystem for neurophysiology data standardization. The lecture also introduces some NWB-enabled tools.
In February 2020, the Canadian government published its "Roadmap for Open Science" to provide overarching principles and recommendations to guide Open Science activities in federally funded scientific research. It outlines broad guidelines for making science in Canada open to all while respecting privacy, security, ethical considerations, and appropriate intellectual property protection.
This lesson provides an introduction the International Neuroinformatics Coordinating Facility (INCF), its mission towards FAIR neuroscience, and future directions.
This talk discusses what are usually considered successful outcomes of scientific research consortia, and how those outcomes can be translated into lasting impacts.
This final lesson of the course consists of the panel discussion for Streamlining Cross-Platform Data Integration session during the first day of INCF's Neuroinformatics Assembly 2023.
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 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 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 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 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.
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.