Leiden Observatory, Leiden University, Leiden, The Netherlands.
Institute of Environmental Sciences (CML), Leiden University, Leiden, The Netherlands.
PLoS One. 2021 Apr 19;16(4):e0249755. doi: 10.1371/journal.pone.0249755. eCollection 2021.
Many citizen science projects depend on colour vision. Examples include classification of soil or water types and biological monitoring. However, up to 1 in 11 participants are colour blind. We simulate the impact of various forms of colour blindness on measurements with the Forel-Ule scale, which is used to measure water colour by eye with a 21-colour scale. Colour blindness decreases the median discriminability between Forel-Ule colours by up to 33% and makes several colour pairs essentially indistinguishable. This reduces the precision and accuracy of citizen science data and the motivation of participants. These issues can be addressed by including uncertainty estimates in data entry forms and discussing colour blindness in training materials. These conclusions and recommendations apply to colour-based citizen science in general, including other classification and monitoring activities. Being inclusive of the colour blind increases both the social and scientific impact of citizen science.
许多公民科学项目依赖于颜色视觉。例如，土壤或水类型的分类以及生物监测。然而，多达 11 分之一的参与者有色盲。我们使用 Forel-Ule 量表模拟各种形式的色盲对测量的影响，该量表用于通过 21 色标用眼睛测量水色。色盲使 Forel-Ule 颜色之间的中位数可辨别性降低了高达 33%，并使一些颜色对几乎无法区分。这降低了公民科学数据的精度和准确性，以及参与者的积极性。通过在数据输入表单中包含不确定性估计值并在培训材料中讨论色盲，可以解决这些问题。这些结论和建议适用于一般的基于颜色的公民科学，包括其他分类和监测活动。包容色盲者可以提高公民科学的社会和科学影响力。
