AtOM, an ontology model for standardizing use of brain atlases in tools, workflows, and data infrastructures

Kleven, Heidi; Martone, Maryann E.; Bjaalie, Jan G.; Zehl, Lyuba; Gillespie, Thomas H.; Leergaard, Trygve B.; Dickscheid, Timo

doi:10.1101/2023.01.22.525049

Preprint

FZJ-2023-01990

AtOM, an ontology model for standardizing use of brain atlases in tools, workflows, and data infrastructures

Kleven, H. (Corresponding author) ; Gillespie, T. H. (Corresponding author) ; Zehl, L.FZJ* ; Dickscheid, T.FZJ* ; Bjaalie, J. G. ; Martone, M. E. ; Leergaard, T. B.

2023

bioarxiv 24 pp. (2023) [10.1101/2023.01.22.525049]

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Please use a persistent id in citations: http://hdl.handle.net/2128/34381 doi:10.1101/2023.01.22.525049

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 standardization 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 propose minimum requirements for FAIR atlases and discuss how AtOM may facilitate atlas interoperability and data integration. 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.

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