Standards and the BICCN: Toward FAIR Neuroscience

The development and adoption of standards is essential to advancing rigorous science and efficient collaboration. To be reused and shared efficiently, accessible data need to be described with standards. Standards development takes many forms from experimental protocols, data formats, computational pipelines to data presentation (1). The development of standards also relies on the software tools being used by the community for the description of the input and output data representations and transformations.   The Brain Cell Data Center (BCDC) promotes the development and use of standards on behalf of the BICCN. Here we document the technical, quality control and policy standards developed or utilized by the BICCN to provide guidance/best-practices for consortia members and others seeking to use BICCN data. 

FAIR data principles specify a set of practices:

  • Persistent identifiers, rich metadata to describe all data sets
  • Detailed provenance, e.g., versions, authors, read mes
  • Adherence to and definition of data standards
  • Provide data attributes to aid reuse, e.g., experimental protocol
  • Use of clear licenses and data use agreements

The BICCN actively supports data processing, mapping, and analysis standards to make all BICCN data FAIR (findable, accessible, informative and reusable). The FAIR data principles specify a set of practices to achieve this (see inset).

The generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN) and was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis (2). This ongoing consortium effort provides an ideal opportunity for describing and promoting FAIR standards in neuroscience. Ongoing work in whole brain profiling in mouse, human, and non-human primates will use these standards for more effective scientific processing, organization, and communication of results.


The collected standards resources here represent the works of individual scientists, data annotators and program management to collect and establish protocols, data and metadata formats, policies, best practices and training.  This site will be updated as new materials are developed.

BICCN Standardization

Data Submission and Publishing

  • For BICCN Consortium members:  Materials to help BICCN members submit their data to the archives (coming soon)
  • Publishing  experimental protocols in use in BICCN (comingn soon)
  • BICCN data policies (coming soon)

Tools and Training

  • Tools and training for using BICCN data, standards and infrastructure (coming soon)
  • Tutorial quick links
    • 2020 BICCN Data Processing Workshop (Terra login, video tutorial)
    • 2021 BICCN Omics Workshop Landing Page (events list)
    • BICCN Omics Virtual Workshop: Find data in NEMO and analyze using Broad pipelines (video)


For more information about BICCN products and standards, visit our GitHub repo.  


  1. Poline JB, Kennedy DN, Sommer FT, Ascoli GA, Van Essen DC, Ferguson AR, et al. Is Neuroscience FAIR? A Call for Collaborative Standardisation of Neuroscience Data. Neuroinformatics. 2022.
  2. Network BICC. A multimodal cell census and atlas of the mammalian primary motor cortex. Nature. 2021;598(7879):86-102.