Vatandaş Bilimi Verilerinin Güvenilirliği: eBird Türkiye’deki Bir Veri Setinin Benford Kanunu ile Test Edilmesi

Abstract

The Reliability of Citizen Science Data: Testing A Data Set from eBird Türkiye with Benford’s Law

Abstract

Citizen science is a rapidly evolving and increasingly popular field of scientific inquiry in which data are collected by volunteers (citizens). Applications of citizen science represent a growing data resource used by researchers, nature conservationists, and public institutions. Although citizen science data can make substantial contributions within the scope of Conservation Biology—particularly to the protection and management of biological diversity, ecosystems, and natural resources—concerns regarding data quality persist, despite the expanding potential of citizen science. Ensuring that data collected through citizen science efforts are accurate and reliable is crucial for conducting valid assessments in Conservation Biology and for enabling more effective conservation practices.In this study, we sought to test the accuracy of bird observation data gathered via the citizen science platform eBird Türkiye (http://www.ebird.org)—which contains observation counts for 533 bird species recorded in Türkiye—by applying Benford’s Law. Benford’s Law is a mathematical approach developed to analyze the distribution of numbers in data sets that may not have a strictly “natural” origin. Additionally, a Chi-Square Goodness-of-Fit Test was conducted to detect differences between the observed (actual) values and the expected (Benford’s Law) values. The results indicate that the tested data from the eBird Türkiye platform conform to Benford’s Law.

Keywords

• Benford Law
• Conversation Biology
• eBird
• Citizen Science
• Biodiversity

References

1. [1]. İçen, H., Kapan, K., & Uysal, A. (2024). Bilimsel araştırma süreçlerinde yeni bir yaklaşım olarak vatandaş bilimi (citizen science). Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 14(3), 1583-1597.
2. [2]. Bonney, R., Cooper, C. B., Dickinson, J., Kelling, S., Phillips, T., Rosenberg, K. V., & Shirk, J. (2009). Citizen science: a developing tool for expanding science knowledge and scientific literacy. BioScience, 59(11), 977-984.
3. [3]. Cooper, C. B., Shirk, J., & Zuckerberg, B. (2014). The invisible prevalence of citizen science in global research: migratory birds and climate change. PLoS ONE, 9(9), e106508. https://doi.org/10.1371/journal.pone.0106508.
4. [4]. Theobald, E. J., Ettinger, A. K., Burgess, H. K., DeBey, L. B., Schmidt, N. R., Froehlich, H. E., ... & Parrish, J. K. (2015). Global change and local solutions: Tapping the unrealized potential of citizen science for biodiversity research. Biological Conservation, 181, 236-244.
5. [5]. Sullivan, B.L., C.L. Wood, M.J. Iliff, R.E. Bonney, D. Fink, and S. Kelling. 2009. eBird: a citizen-based bird observation network in the biological sciences. Biological Conservation 142: 2282-2292.
6. [6]. Chandler, M., See, L., Copas, K., Bonde, A. M., López, B. C., Danielsen, F., ... & Turak, E. (2017). Contribution of citizen science towards international biodiversity monitoring. Biological conservation, 213, 280-294.
7. [7]. Pocock, M. J., Chandler, M., Bonney, R., Thornhill, I., Albin, A., August, T., ... & Danielsen, F. (2018). A vision for global biodiversity monitoring with citizen science. In Advances in ecological research (Vol. 59, pp. 169-223). Academic Press.
8. [8]. Meyer, C., Kreft, H., Guralnick, R., & Jetz, W. (2015). Global priorities for an effective information basis of biodiversity distributions. Nature communications, 6(1), 1-8.

9. [9]. Burgess, H. K., DeBey, L. B., Froehlich, H. E., Schmidt, N., Theobald, E. J., Ettinger, A. K., ... & Parrish, J. K. (2017). The science of citizen science: Exploring barriers to use as a primary research tool. Biological Conservation, 208, 113-120.
10. [10]. Hortal, J., Jiménez‐Valverde, A., Gómez, J. L. G., Lobo, J. M., & Baselga, A. (2008). Historical bias in biodiversity inventories affects the observed environmental niche of the species. Oikos, 117(6), 847-858. https://doi.org/10.1111/j.0030-1299.2008.16434.x.
11. [11]. Szabo, J. K., Khwaja, N., Garnett, S. T., & Butchart, S. H. (2012). Global patterns and drivers of avian extinctions at the species and subspecies level.
12. [12]. Ward, D. F. (2014). Understanding sampling and taxonomic biases recorded by citizen scientists. Journal of insect conservation, 18, 753-756.
13. [13]. Troudet, J., Grandcolas, P., Blin, A., Vignes-Lebbe, R., & Legendre, F. (2017). Taxonomic bias in biodiversity data and societal preferences. Scientific reports, 7(1), 9132.
14. [14]. Primack, R. B. (2006). Essentials of conservation biology (Vol. 23). Sunderland: Sinauer Associates.
15. [15]. Newcomb, S. (1881). Astronomical observatories. Science, (59), 377-380.
16. [16]. Benford, F. (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, 551-572.
17. [17]. Cerri, J., Testa, F., & Rizzi, F. (2018). The more I care, the less I will listen to you: How information, environmental concern and ethical production influence consumers' attitudes and the purchasing of sustainable products. Journal of Cleaner Production, 175, 343-353.
18. [18]. Perazzoni, F., Bacelar-Nicolau, P., & Painho, M. (2020). Correction: Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon. ISPRS Int. J. Geo-Inf. 2020, 9, 398. ISPRS International Journal of Geo-Information, 9(10), 573.
19. [19]. Costas, R., & Bordons, M. (2008). Is g-index better than h-index? An exploratory study at the individual level. Scientometrics, 77(2), 267-288.
20. [20]. Docampo, S., del Mar Trigo, M., Aira, M. J., Cabezudo, B., & Flores-Moya, A. (2009). Benford’s law applied to aerobiological data and its potential as a quality control tool. Aerobiologia, 25, 275-283.
21. [21]. Friar, J. L., Goldman, T., & Pérez–Mercader, J. (2012). Genome sizes and the Benford distribution. PLoS One, 7(5), e36624.
22. [22]. Campos, L., Salvo, A. E., & Flores-Moya, A. (2016). Natural taxonomic categories of angiosperms obey Benford's law, but artificial ones do not. Systematics and Biodiversity, 14(5), 431-440.
23. [23]. Özkundakci, D., & Pingram, M. A. (2019). Nature favours “one” as the leading digit in phytoplankton abundance data. Limnologica, 78, 125707.
24. [24]. Özkan K. Estimating ecosystem naturalness using Benford’s Law and Generalized Benford’s Law. Turkish Journal of Forestry. Haziran 2021;22(2):73-82. doi:10.18182/tjf.907217
25. [25]. Michener, W. K. (2006). Meta-information concepts for ecological data management. Ecological informatics, 1(1), 3-7.
26. [26]. Dickinson, J. L., Shirk, J., Bonter, D., Bonney, R., Crain, R. L., Martin, J., ... & Purcell, K. (2012). The current state of citizen science as a tool for ecological research and public engagement. Frontiers in Ecology and the Environment, 10(6), 291-297.
27. [27]..eBird. (2024). eBird: An online database of bird distribution and abundance [https://ebird.org/data/download?p=ebd_TR_202301_202312_relOct-2024.zip]. eBird, Cornell Lab of Ornithology, Ithaca, New York. Available: http://www.ebird.org. (Accessed: October 25, 2024).
28. [28]. Türkyener, C.M. “Benford Yasası ve Mali Denetimde Kullanımı”, Sayıştay Dergisi, Ocak-Mart 2007, 64:111-122.
29. [29]..Fournier, A. M., Sullivan, A. R., Bump, J. K., Perkins, M., Shieldcastle, M. C., & King, S. L. (2017). Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive V irginia rail. Journal of Applied Ecology, 54(2), 618-627.
30. [30]. Kosmala, M., Wiggins, A., Swanson, A., and Simmons, B. (2016). Assessing data quality in citizen science. Front Ecol Environ 2016; 14(10): 551–560, doi:10.1002/fee.1436