Bias in Open Biodiversity Data: Methodological Implications for Conservation Decision-Making

Keywords:
Open Data, Data Bias, Citizen Science, Nature Conservation, Biodiversity

Abstract:
Modern nature conservation increasingly relies on open biodiversity data, especially on species occurrence records from digital platforms, collections, monitoring programs, and citizen science. These datasets can cover large areas and long time periods. However, their analytical value depends not only on data volume, but also on representativeness, metadata quality, and the way they were collected. One of the main problems is bias, because some areas, taxonomic groups, time periods, and observer types generate far more records than others. As a result, open data can give a distorted picture of biodiversity and affect models, trend estimates, and conservation priorities. This paper reviews the main forms of bias and links them with their effects on analytical results and decision-making. It concludes that open biodiversity data are highly valuable for modern nature conservation, but their analytical and practical value depends on careful methodological use and a clear understanding of their limits.

CITATION:

IEEE format

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J. Đukić, D. Cvetković, “Bias in Open Biodiversity Data: Methodological Implications for Conservation Decision-Making,” in Sinteza 2026 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2026, pp. 570-576. doi:10.15308/Sinteza-2026-570-576

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Đukić, J., Cvetković, D. (2026). Bias in Open Biodiversity Data: Methodological Implications for Conservation Decision-Making. Paper presented at Sinteza 2026 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2026-570-576

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