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Harmonizing the Generation and Pre-publication Stewardship of FAIR bioimage data.

Authors :
Bialy N
Alber F
Andrews B
Angelo M
Beliveau B
Bintu L
Boettiger A
Boehm U
Brown CM
Maina MB
Chambers JJ
Cimini BA
Eliceiri K
Errington R
Faklaris O
Gaudreault N
Germain RN
Goscinski W
Grunwald D
Halter M
Hanein D
Hickey JW
Lacoste J
Laude A
Lundberg E
Ma J
Malacrida L
Moore J
Nelson G
Neumann EK
Nitschke R
Onami S
Pimentel JA
Plant AL
Radtke AJ
Sabata B
Schapiro D
Schöneberg J
Spraggins JM
Sudar D
Vierdag WAM
Volkmann N
Wählby C
Wang SS
Yaniv Z
Strambio-De-Castillia C
Source :
ArXiv [ArXiv] 2024 Aug 30. Date of Electronic Publication: 2024 Aug 30.
Publication Year :
2024

Abstract

Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured bioimage data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable bioimage data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled "Enabling Global Image Data Sharing in the Life Sciences," which is published in parallel and addresses the need to build the cyberinfrastructure for sharing bioimage data (arXiv:2401.13023 [q-bio.OT], https://doi.org/10.48550/arXiv.2401.13023). Here, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse bioimage data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made generating community standard practices for imaging Quality Control (QC) and metadata (Faklaris et al., 2022; Hammer et al., 2021; Huisman et al., 2021; Microscopy Australia , 2016; Montero Llopis et al., 2021; Rigano et al., 2021; Sarkans et al., 2021). We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges and democratize access to common practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.<br />Competing Interests: Conflict of Interest Statements Below are the statements shared by contributors indicating potential conflict of interest. NameStatementUlrike BoehmUB’s contribution to this manuscript is a result of her voluntary involvement with QUAREP-LiMi and BINA, and does not reflect the position of Carl Zeiss AG on this matter.Josh Mooreholds equity in Glencoe Software.Denis SchapiroDS reports funding from GSK and received honorariums from Immunai, Noetik, Alpenglow and Lunaphore.Damir SudarDSu is employed by Quantitative Imaging Systems, a commercial entity developing imaging software.Siyuan (Steven) WangFounder, shareholder, consultant of Translura, Inc

Details

Language :
English
ISSN :
2331-8422
Database :
MEDLINE
Journal :
ArXiv
Publication Type :
Academic Journal
Accession number :
38351940