AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures
Abstract Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions,...
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Language: | English |
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Nature Portfolio
2023-07-01
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Series: | Scientific Data |
Online Access: | https://doi.org/10.1038/s41597-023-02389-4 |
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author | Heidi Kleven Thomas H. Gillespie Lyuba Zehl Timo Dickscheid Jan G. Bjaalie Maryann E. Martone Trygve B. Leergaard |
author_facet | Heidi Kleven Thomas H. Gillespie Lyuba Zehl Timo Dickscheid Jan G. Bjaalie Maryann E. Martone Trygve B. Leergaard |
author_sort | Heidi Kleven |
collection | DOAJ |
description | Abstract Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data. |
first_indexed | 2024-03-12T21:12:02Z |
format | Article |
id | doaj.art-7bb7689a823a467ea14f29d8ec3ed1cd |
institution | Directory Open Access Journal |
issn | 2052-4463 |
language | English |
last_indexed | 2024-03-12T21:12:02Z |
publishDate | 2023-07-01 |
publisher | Nature Portfolio |
record_format | Article |
series | Scientific Data |
spelling | doaj.art-7bb7689a823a467ea14f29d8ec3ed1cd2023-07-30T11:07:01ZengNature PortfolioScientific Data2052-44632023-07-0110111110.1038/s41597-023-02389-4AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructuresHeidi Kleven0Thomas H. Gillespie1Lyuba Zehl2Timo Dickscheid3Jan G. Bjaalie4Maryann E. Martone5Trygve B. Leergaard6Department of Molecular Medicine, Institute of Basic Medical Sciences, University of OsloDepartment of Neurosciences, University of CaliforniaInstitute of Neuroscience and Medicine (INM-1), Research Centre JülichInstitute of Neuroscience and Medicine (INM-1), Research Centre JülichDepartment of Molecular Medicine, Institute of Basic Medical Sciences, University of OsloDepartment of Neurosciences, University of CaliforniaDepartment of Molecular Medicine, Institute of Basic Medical Sciences, University of OsloAbstract Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.https://doi.org/10.1038/s41597-023-02389-4 |
spellingShingle | Heidi Kleven Thomas H. Gillespie Lyuba Zehl Timo Dickscheid Jan G. Bjaalie Maryann E. Martone Trygve B. Leergaard AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures Scientific Data |
title | AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures |
title_full | AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures |
title_fullStr | AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures |
title_full_unstemmed | AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures |
title_short | AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures |
title_sort | atom an ontology model to standardize use of brain atlases in tools workflows and data infrastructures |
url | https://doi.org/10.1038/s41597-023-02389-4 |
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