A Mobile Application–Based Citizen Science Product to Compile Bird Observations
Nokelainen, Ossi; Schiestl-Aalto, Pauliina; Lauha, Patrik; Somervuo, Panu; Andrejeff, Sebastian; Sundell, Janne; Hänninen, Jari; Talaskivi, Jussi; Inkinen, Jasmin; Vallinmäki, Mikko; Kallio, Aleksi; Vancraeyenest, Aurélie; Lehto, Harry J.; Lehtiö, Ari; Mutanen, Marko; Ovaskainen, Otso; Paavola, Riku (2024-09-10)
Ubiquity Press
10.09.2024
Nokelainen, O, Lauha, P, Andrejeff, S, Hänninen, J, Inkinen, J, Kallio, A, Lehto, HJ, Mutanen, M, Paavola, R, Schiestl-Aalto, P, Somervuo, P, Sundell, J, Talaskivi, J, Vallinmäki, M, Vancraeyenest, A, Lehtiö, A and Ovaskainen, O. 2024. A Mobile Application–Based Citizen Science, Product to Compile Bird Observations. Citizen Science: Theory and Practice, 9(1): 24, pp. 1–14. DOI: https://doi.org/10.5334/cstp.710
https://creativecommons.org/licenses/by/4.0/
© 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
© 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202409236022
https://urn.fi/URN:NBN:fi:oulu-202409236022
Tiivistelmä
Abstract
Citizen science covers initiatives from crowdsourcing, distributed intelligence, and participatory science, to extreme citizen science. Terminological overlap, varied project aims, and cultural differences in the fields of research have, however, led to discord regarding how impactful citizen science projects can be. Here, we showcase a mobile application–based citizen science campaign (in Finnish: Muuttolintujen kevät), an automated bird sound classifier of Finnish birds. Over a single season (2023), the method attracted 140,000 participants who uploaded close to three million recordings containing six million bird observations. We report the spatial and temporal distribution of the observations collected, characterize the user behaviour, and discuss reliability of the user-based validations of the AI-powered species identifications. To circumvent data quality problems that characterize many citizen science projects, our approach stores the raw audio in a centralized repository, enabling rigorous validation and re-analysis. Mobile application-based citizen science initiatives can be harnessed to probe the state of our environment almost in real time and potentially guide conservation acts in the future.
Citizen science covers initiatives from crowdsourcing, distributed intelligence, and participatory science, to extreme citizen science. Terminological overlap, varied project aims, and cultural differences in the fields of research have, however, led to discord regarding how impactful citizen science projects can be. Here, we showcase a mobile application–based citizen science campaign (in Finnish: Muuttolintujen kevät), an automated bird sound classifier of Finnish birds. Over a single season (2023), the method attracted 140,000 participants who uploaded close to three million recordings containing six million bird observations. We report the spatial and temporal distribution of the observations collected, characterize the user behaviour, and discuss reliability of the user-based validations of the AI-powered species identifications. To circumvent data quality problems that characterize many citizen science projects, our approach stores the raw audio in a centralized repository, enabling rigorous validation and re-analysis. Mobile application-based citizen science initiatives can be harnessed to probe the state of our environment almost in real time and potentially guide conservation acts in the future.
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