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

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 t...

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Autores principales: Smith, Patricia, King, Oliver N. F., Pennington, Avery, Tun, Win, Basham, Mark, Jones, Martin L., Collinson, Lucy M., Darrow, Michele C., Spiers, Helen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245346/
https://www.ncbi.nlm.nih.gov/pubmed/37284846
http://dx.doi.org/10.1007/s00418-023-02204-6
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author Smith, Patricia
King, Oliver N. F.
Pennington, Avery
Tun, Win
Basham, Mark
Jones, Martin L.
Collinson, Lucy M.
Darrow, Michele C.
Spiers, Helen
author_facet Smith, Patricia
King, Oliver N. F.
Pennington, Avery
Tun, Win
Basham, Mark
Jones, Martin L.
Collinson, Lucy M.
Darrow, Michele C.
Spiers, Helen
author_sort Smith, Patricia
collection PubMed
description 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.
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spelling pubmed-102453462023-06-08 Online citizen science with the Zooniverse for analysis of biological volumetric data Smith, Patricia King, Oliver N. F. Pennington, Avery Tun, Win Basham, Mark Jones, Martin L. Collinson, Lucy M. Darrow, Michele C. Spiers, Helen Histochem Cell Biol Original Paper 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. Springer Berlin Heidelberg 2023-06-07 2023 /pmc/articles/PMC10245346/ /pubmed/37284846 http://dx.doi.org/10.1007/s00418-023-02204-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Smith, Patricia
King, Oliver N. F.
Pennington, Avery
Tun, Win
Basham, Mark
Jones, Martin L.
Collinson, Lucy M.
Darrow, Michele C.
Spiers, Helen
Online citizen science with the Zooniverse for analysis of biological volumetric data
title Online citizen science with the Zooniverse for analysis of biological volumetric data
title_full Online citizen science with the Zooniverse for analysis of biological volumetric data
title_fullStr Online citizen science with the Zooniverse for analysis of biological volumetric data
title_full_unstemmed Online citizen science with the Zooniverse for analysis of biological volumetric data
title_short Online citizen science with the Zooniverse for analysis of biological volumetric data
title_sort online citizen science with the zooniverse for analysis of biological volumetric data
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245346/
https://www.ncbi.nlm.nih.gov/pubmed/37284846
http://dx.doi.org/10.1007/s00418-023-02204-6
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