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Designing online species identification tools for biological recording: the impact on data quality and citizen science learning

Sharma, Nirwan; Colucci-Gray, Laura; Siddharthan, Advaith; Comont, Richard and Van der Wal, René (2019). Designing online species identification tools for biological recording: the impact on data quality and citizen science learning. PeerJ, 6, article no. e5965.

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In recent years, the number and scale of environmental citizen science programmes that involve lay people in scientific research have increased rapidly. Many of these initiatives are concerned with the recording and identification of species, processes which are increasingly mediated through digital interfaces. Here, we address the growing need to understand the particular role of digital identification tools, both in generating scientific data and in supporting learning by lay people engaged in citizen science activities pertaining to biological recording communities. Starting from two well-known identification tools, namely identification keys and field guides, this study focuses on the decision-making and quality of learning processes underlying species identification tasks, by comparing three digital interfaces designed to identify bumblebee species. The three interfaces varied with respect to whether species were directly compared or filtered by matching on visual features; and whether the order of filters was directed by the interface or a user-driven open choice. A concurrent mixed-methods approach was adopted to compare how these different interfaces affected the ability of participants to make correct and quick species identifications, and to better understand how participants learned through using these interfaces. We found that the accuracy of identification and quality of learning were dependent upon the interface type, the difficulty of the specimen on the image being identified and the interaction between interface type and ‘image difficulty’. Specifically, interfaces based on filtering outperformed those based on direct visual comparison across all metrics, and an open choice of filters led to higher accuracy than the interface that directed the filtering. Our results have direct implications for the design of online identification technologies for biological recording, irrespective of whether the goal is to collect higher quality citizen science data, or to support user learning and engagement in these communities of practice.

Item Type: Journal Item
Copyright Holders: 2019 The Authors
ISSN: 2167-8359
Keywords: citizen science; user learning; species identification; identification keys; field guides; data quality; learning; cognition; bumblebees; biological recording
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 58869
Depositing User: Advaith Siddharthan
Date Deposited: 28 Jan 2019 11:17
Last Modified: 04 May 2019 20:28
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