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利用 Zooniverse 开展在线公民科学,分析生物体积数据。

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

机构信息

The Rosalind Franklin Institute, Harwell Campus, Fermi Avenue, Didcot, OX11 0FA, UK.

Diamond Light Source, Harwell Campus, Fermi Avenue, Didcot, OX11 0DE, UK.

出版信息

Histochem Cell Biol. 2023 Sep;160(3):253-276. doi: 10.1007/s00418-023-02204-6. Epub 2023 Jun 7.

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.

摘要

公众参与研究,也被称为公民科学,越来越多地被用于分析生物体积数据。该领域的研究人员正在将在线公民科学作为一种可扩展的分布式数据分析方法,最近的研究表明,非专业人士可以有效地参与到诸如在电子显微镜数据中分割细胞器等任务中。这一点,以及现在常规产生的大量生物体积数据需要快速处理的日益增长的挑战,意味着研究界越来越有兴趣将在线公民科学应用于这种情况下的数据分析。在这里,我们综合了应用公民科学分析生物体积数据的核心方法原则和实践。我们收集和分享了多个研究团队的知识和经验,这些团队使用 Zooniverse 平台(www.zooniverse.org)将在线公民科学应用于体积生物数据的分析。我们希望这能为如何通过在线公民科学有效地应用于该领域的贡献者努力提供灵感和实际指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9779/10492696/2bea549f586c/418_2023_2204_Fig1_HTML.jpg

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