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Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability

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. H...

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Autores principales: Sanchez, Morgan, Moore, Dymon, Johnson, Erik C., Wester, Brock, Lichtman, Jeff W., Gray-Roncal, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150677/
https://www.ncbi.nlm.nih.gov/pubmed/35651719
http://dx.doi.org/10.3389/fninf.2022.828458
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author Sanchez, Morgan
Moore, Dymon
Johnson, Erik C.
Wester, Brock
Lichtman, Jeff W.
Gray-Roncal, William
author_facet Sanchez, Morgan
Moore, Dymon
Johnson, Erik C.
Wester, Brock
Lichtman, Jeff W.
Gray-Roncal, William
author_sort Sanchez, Morgan
collection PubMed
description 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.
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spelling pubmed-91506772022-05-31 Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability Sanchez, Morgan Moore, Dymon Johnson, Erik C. Wester, Brock Lichtman, Jeff W. Gray-Roncal, William Front Neuroinform Neuroscience 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. Frontiers Media S.A. 2022-05-16 /pmc/articles/PMC9150677/ /pubmed/35651719 http://dx.doi.org/10.3389/fninf.2022.828458 Text en Copyright © 2022 Sanchez, Moore, Johnson, Wester, Lichtman and Gray-Roncal. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Sanchez, Morgan
Moore, Dymon
Johnson, Erik C.
Wester, Brock
Lichtman, Jeff W.
Gray-Roncal, William
Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability
title Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability
title_full Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability
title_fullStr Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability
title_full_unstemmed Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability
title_short Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability
title_sort connectomics annotation metadata standardization for increased accessibility and queryability
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150677/
https://www.ncbi.nlm.nih.gov/pubmed/35651719
http://dx.doi.org/10.3389/fninf.2022.828458
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