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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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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. |
format | Online Article Text |
id | pubmed-9150677 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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