BSG‐BATS: An open‐source data annotation portal and classifier for European bat vocalizations

Abstract Bats are ecologically important mammals whose monitoring increasingly relies on acoustic data. However, many tools for bat call identification remain subscription‐based, closed‐source, region‐specific or limited in scalability, creating barriers to global data integration and method development. We present BSG‐BATS, an open‐access annotation portal and convolutional neural network (CNN)‐based classifier for bat calls. The portal enables researchers and practitioners to annotate calls at species or phonic group level and contribute directly to the iterative improvement of the classifier. As a proof of concept, we trained the first BSG‐BATS model using over 4000 annotated recordings of 21 European species. It gave promising results and outperformed many commonly used commercial and academic tools by providing higher AUC (area under the receiver operating characteristic curve) scores for test data. All annotations are transparently annotated in the portal ( https://bsg.laji.fi/bats/identification/instructions ) and the trained model, code and documentation are available at www.zenodo.org/records/15495676 . BSG‐BATS offers a foundation for community‐driven development of bat sound identification tools. By integrating annotation and model retraining on an open‐access platform, it enables collective improvement and adaptation to new regions, species and sound types. We invite all bat researchers and experts to join this collaborative effort, whether by contributing data ( [email protected] ), annotating sounds ( https://bsg.laji.fi/bats/identification/instructions ) or testing the model in their own work ( https://www.zenodo.org/records/15495676 ).

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Publication Details

Journal
Methods in Ecology and Evolution
Published
2025-12-08
DOI
https://doi.org/10.1111/2041-210x.70220
Primary Topic
Bat Biology and Ecology Studies
Type
article
Field-Weighted Citation Impact
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article

BSG‐BATS: An open‐source data annotation portal and classifier for European bat vocalizations

Panu Somervuo, Thomas M. Lilley, Meeri Rannisto, Otso Ovaskainen et al.
Methods in Ecology and Evolution
Bat Biology and Ecology Studies
article

BSG‐BATS: An open‐source data annotation portal and classifier for European bat vocalizations

Panu Somervuo, Thomas M. Lilley, Meeri Rannisto, Otso Ovaskainen, Adrià López‐Baucells, Tomas V. Roslin, Fabrizio Gili, Patrik Lauha, Katarina Meramo
article en

Abstract

Abstract Bats are ecologically important mammals whose monitoring increasingly relies on acoustic data. However, many tools for bat call identification remain subscription‐based, closed‐source, region‐specific or limited in scalability, creating barriers to global data integration and method development. We present BSG‐BATS, an open‐access annotation portal and convolutional neural network (CNN)‐based classifier for bat calls. The portal enables researchers and practitioners to annotate calls at species or phonic group level and contribute directly to the iterative improvement of the classifier. As a proof of concept, we trained the first BSG‐BATS model using over 4000 annotated recordings of 21 European species. It gave promising results and outperformed many commonly used commercial and academic tools by providing higher AUC (area under the receiver operating characteristic curve) scores for test data. All annotations are transparently annotated in the portal ( https://bsg.laji.fi/bats/identification/instructions ) and the trained model, code and documentation are available at www.zenodo.org/records/15495676 . BSG‐BATS offers a foundation for community‐driven development of bat sound identification tools. By integrating annotation and model retraining on an open‐access platform, it enables collective improvement and adaptation to new regions, species and sound types. We invite all bat researchers and experts to join this collaborative effort, whether by contributing data ( [email protected] ), annotating sounds ( https://bsg.laji.fi/bats/identification/instructions ) or testing the model in their own work ( https://www.zenodo.org/records/15495676 ).

Methods in Ecology and EvolutionVol. 17(3)
University of Helsinki (FI), Swedish University of Agricultural Sciences (SE), Hospital General de Granollers (ES), Finnish Museum of Natural History (FI), National Research Council (IT), University of Jyväskylä (FI)
Openalex Percentile: Top 71%
Bat Biology and Ecology Studies
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