Everyone counts? Design considerations in online citizen science

Abstract

Effective classification of large datasets is a ubiquitous challenge across multiple knowledge domains. One solution gaining in popularity is to perform distributed data analysis via online citizen science platforms, such as the Zooniverse. The resulting growth in project numbers is increasing the need to improve understanding of the volunteer experience; as the sustainability of citizen science is dependent on our ability to design for engagement and usability. Here, we examine volunteer interaction with 63 projects, representing the most comprehensive collection of online citizen science project data gathered to date. Together, this analysis demonstrates how subtle project design changes can influence many facets of volunteer interaction, including when and how much volunteers interact, and, importantly, who participates. Our findings highlight the tension between designing for social good and broad community engagement, versus optimizing for scientific and analytical efficiency.

Citizen science breathes new life into participatory agricultural research. A review

“…For example, Sturm and Tscholl (2019) indicated the importance of user feedback for participatory design approaches by distinguishing between general user feedback, contributory user feedback and co-creational user feedback to be able to cater for different types of volunteers. Spiers et al (2019) explore user issues and volunteer behavior in 63 online citizen science projects and found that many subtle design choices influence how and how much interaction takes place and, ultimately, who participates or not. Skarlatidou et al (2019b) present a series of highly specific design considerations based on a systematic review of the literature and conclude that user studies should be fully integrated in any citizen science project design.…”

Citizen science, cells and CNNs – deep learning for automatic segmentation of the nuclear envelope in electron microscopy data, trained with volunteer segmentations

“…As classifications could be made by unregistered volunteers, it was not possible to establish precisely how many individuals contributed, however, classifications submitted by logged in users were associated with n = 4749 user ids and n = 9444 IP addresses, indicating between 5000 -10000 individuals contributed. As is often observed for online citizen science projects [18], a large number of classifications were received shortly after project launch ( Supplementary Fig. 3A), and the number of classifications submitted by each volunteer varied greatly (from 1 to 5451), indicating a broad range of engagement levels amongst the community contributing to this project ( Supplementary Fig.…”

“…Examining the Lorenz curve for the distribution of volunteer classification contributions to the project ( Supplementary Fig. 3C) and the corresponding Gini coefficient (0.83), indicated that a small number of volunteers contributed a large number of classifications, as is commonly observed in citizen science projects [18]. However, it should be noted that a significant proportion of the classifications submitted to the project were made by individuals only submitting a small number, reiterating the importance of all individual contributions.…”

Citizen Science and Biological Invasions: A Review

“…The methods used in citizen science projects should strive to maximize the reach and engagement of a broader audience (e.g., field sampling, social media, in-person interviews/ questionnaires). For example, digital platforms of communication between citizen scientists and scientists exclude those that are not technologically savvy, despite being very effective and essential in modern citizen science projects (Spiers et al, 2019). This is a simple example of why multiple methods must be set in place.…”