Standard metadata for 3D microscopy

Autor: Alexander J. Ropelewski, Megan A. Rizzo, Jason R. Swedlow, Jan Huisken, Pavel Osten, Neda Khanjani, Kurt Weiss, Vesselina Bakalov, Michelle Engle, Lauren Gridley, Michelle Krzyzanowski, Tom Madden, Deborah Maiese, Meisha Mandal, Justin Waterfield, David Williams, Carol M. Hamilton, Wayne Huggins
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Scientific Data, Vol 9, Iss 1, Pp 1-8 (2022)
Druh dokumentu: article
ISSN: 2052-4463
DOI: 10.1038/s41597-022-01562-5
Popis: Abstract Recent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function. These experiments’ images make it possible to catalog brain cell types and define their location, morphology, and connectivity in a native context, leading to a better understanding of normal development and disease etiology. Consistent annotation of metadata is needed to provide the context necessary to understand, reuse, and integrate these data. This report describes an effort to establish metadata standards for three-dimensional (3D) microscopy datasets for use by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative and the neuroscience research community. These standards were built on existing efforts and developed with input from the brain microscopy community to promote adoption. The resulting 3D Microscopy Metadata Standards (3D-MMS) includes 91 fields organized into seven categories: Contributors, Funders, Publication, Instrument, Dataset, Specimen, and Image. Adoption of these metadata standards will ensure that investigators receive credit for their work, promote data reuse, facilitate downstream analysis of shared data, and encourage collaboration.
Databáze: Directory of Open Access Journals