This Working Group coordinates common efforts for defining and describing cell types across neuroscience, to reduce duplicate efforts and to improve interoperability and reuse of cell type-specific data collected across groups. The key focus is facilitating interactions between groups collecting large-scale datasets used to define novel cell types (such as single-cell transcriptomics) and ontologists and tool developers who have considerable experience curating cell type-specific data, with the goal to reduce duplicate efforts and to improve interoperability and reuse of cell type-specific data collected across groups.
The coordination of this effort has now moved to the Allen Institute, as part of their work on cell nomenclatures which began with the Cell Type Ontology Workshop held at the Allen Institute in Seattle in 2019. The outcome of the workshop was a framework for developing nomenclature: the Common Cell Type Nomenclature, or CCN. It was initially applied to brain cells and types, and intended to encompass existing naming strategies used in publications across diverse research teams, to allow tracking of many different taxonomies across diverse areas of bioscience. The CCN is described in this 2020 paper in eLife. To learn more about the current activities of the CCN, visit: https://portal.brain-map.org/explore/classes/nomenclature.
This Working Group coordinates community efforts for the development of open, use case- driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data. It uses provenance information to define the context from which scientific data was generated, including the type of data, its significance, quality and potential for integration and reuse. Data models have been developed thus far for electrophysiology, neuron morphology, brain atlases, and computational modelling. Future developments could include brain imaging, transcriptomic and clinical form data, as determined by the Working Group membership and community interests.
This Working Group formed as the result of a merger of several INCF Working Groups working in the areas of neuroimaging and reproducibility. The group has several separate projects that all have reproducibility in neuroimaging as an overarching theme, specifically focusing on data sharing, data management, and data description. The working group is composed of 3 task forces: Brain Imaging Informatics (NIDASH), Brain Imaging Data Structure (BIDS), Neuroimaging Data Model (NIDM).