Online citizen science with the Zooniverse for analysis of biological volumetric data.

Content Provider	Europe PMC
Author	Smith, Patricia King, Oliver N. F. Pennington, Avery Tun, Win Basham, Mark Jones, Martin L. Collinson, Lucy M. Darrow, Michele C. Spiers, Helen
Abstract	Public participation in research, also known as citizen science, is being increasingly adopted for the analysis of biological volumetric data. Researchers working in this domain are applying online citizen science as a scalable distributed data analysis approach, with recent research demonstrating that non-experts can productively contribute to tasks such as the segmentation of organelles in volume electron microscopy data. This, alongside the growing challenge to rapidly process the large amounts of biological volumetric data now routinely produced, means there is increasing interest within the research community to apply online citizen science for the analysis of data in this context. Here, we synthesise core methodological principles and practices for applying citizen science for analysis of biological volumetric data. We collate and share the knowledge and experience of multiple research teams who have applied online citizen science for the analysis of volumetric biological data using the Zooniverse platform (www.zooniverse.org). We hope this provides inspiration and practical guidance regarding how contributor effort via online citizen science may be usefully applied in this domain.
Related Links	https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC10245346&blobtype=pdf
ISSN	09486143
Journal	Histochemistry and Cell Biology [Histochem Cell Biol]
Volume Number	160
DOI	10.1007/s00418-023-02204-6
PubMed Central reference number	PMC10245346
Issue Number	3
PubMed reference number	37284846
e-ISSN	1432119X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2023-06-07
Publisher Place	Berlin/Heidelberg
Access Restriction	Open
Rights License	Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2023
Subject Keyword	Volume electron microscopy Citizen science Crowdsourcing Segmentation Image processing Machine learning Cell biology Cellular imaging Image classification
Content Type	Text
Resource Type	Article
Subject	Cell Biology Histology Molecular Biology Medical Laboratory Technology