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2022

Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability


Abstract

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.


Citation

AUTHOR=Sanchez Morgan Moore Dymon Johnson Erik C. Wester Brock Lichtman Jeff W. Gray-Roncal William TITLE=Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability JOURNAL=Frontiers in Neuroinformatics VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/articles/10.3389/fninf.2022.828458 DOI=10.3389/fninf.2022.828458 ISSN=1662-5196

Citation

AUTHOR=Sanchez Morgan Moore Dymon Johnson Erik C. Wester Brock Lichtman Jeff W. Gray-Roncal William TITLE=Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability JOURNAL=Frontiers in Neuroinformatics VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/articles/10.3389/fninf.2022.828458 DOI=10.3389/fninf.2022.828458 ISSN=1662-5196