EVApeCognition: an 18-year dataset of great ape cognition
Article
Sánchez-Amaro, A., Ebel van Wijk, S.J., Molenaar, C., Abuova, A., Mujica-Manrique, L., Leisterer-Peoples, S.M., Beheim, B., Maurits, L., Albiach-Serrano, A., Allritz, M., Altınok, N., Amici, F., Auersperg, A.M.I., Aureli, F., Bandini, E., Barth, J., Benziad, L., Bläsing, B.E., Bohn, M., Bourjade, M., Bräuer, J., Broihanne, M.-H., Brosnan, S.F., Bueno-Guerra, N., Bugnyar, T., Buttelmann, D., Buttelmann, F., Cacchione, T., Carpenter, M., Colmenares, F., Crockford, C., Cronin, K.A., de las Heras, A., De Marco, A., DeTroy, S.E., Dufour, V., Duguid, S., Dunbar, R.I.M., Eckert, J., Engelmann, J.M., Fagot, J., Fischer, J., Forss, S.I.F., Funk, M., Gergely, G., Greenberg, J.R., Großmann, J., Grüneisen, S., Halina, M., Hanus, D., Heilbronner, S.R., Heintz, C., Hepach, R., Hermann, E., Hirata, S., Hribar, A., Janzen, G., Kaminski, J., Kanngieser, P., Kano, F., Kirchhofer, K.C., Knofe, H., Kopp, K.S., Krupenye, C., Laumer, I.B., Levinson, S.C., Liszkowski, U., Manrique, H.M., Martin-Ordas, G., McEwen, E.S., Moore, R.T., Munar, E., Nadal, M., Nawroth, C., Nolte, S., Pelé, M., Potì, P., Rakoczy, H., Riedel, J., Romain, A., Rossano, F., Russell, Y., Sabbatini, G., Schäfer, M., Scheumann, M., Schmelz, M., Schmid, B., Schmitt, V., Sebastián-Enesco, C., Seed, A.M., Suda-King, C., Tauzin, T., Tempelmann, S., Tennie. C., Truppa, V., Uher, J., Vaish, A., van Leeuwen, E.J.C., Visalberghi, E.M., Völter, C.J., Vonau, V., Wascher, C.A.F., Wittig, R.M., Wolf, W., Tomasello, M., Liebal, K., Call, J. and Haun, D.B.M. 2026. EVApeCognition: an 18-year dataset of great ape cognition. Scientific Data. https://doi.org/10.1038/s41597-026-07191-6
| Type | Article |
|---|---|
| Title | EVApeCognition: an 18-year dataset of great ape cognition |
| Authors | Sánchez-Amaro, A., Ebel van Wijk, S.J., Molenaar, C., Abuova, A., Mujica-Manrique, L., Leisterer-Peoples, S.M., Beheim, B., Maurits, L., Albiach-Serrano, A., Allritz, M., Altınok, N., Amici, F., Auersperg, A.M.I., Aureli, F., Bandini, E., Barth, J., Benziad, L., Bläsing, B.E., Bohn, M., Bourjade, M., Bräuer, J., Broihanne, M.-H., Brosnan, S.F., Bueno-Guerra, N., Bugnyar, T., Buttelmann, D., Buttelmann, F., Cacchione, T., Carpenter, M., Colmenares, F., Crockford, C., Cronin, K.A., de las Heras, A., De Marco, A., DeTroy, S.E., Dufour, V., Duguid, S., Dunbar, R.I.M., Eckert, J., Engelmann, J.M., Fagot, J., Fischer, J., Forss, S.I.F., Funk, M., Gergely, G., Greenberg, J.R., Großmann, J., Grüneisen, S., Halina, M., Hanus, D., Heilbronner, S.R., Heintz, C., Hepach, R., Hermann, E., Hirata, S., Hribar, A., Janzen, G., Kaminski, J., Kanngieser, P., Kano, F., Kirchhofer, K.C., Knofe, H., Kopp, K.S., Krupenye, C., Laumer, I.B., Levinson, S.C., Liszkowski, U., Manrique, H.M., Martin-Ordas, G., McEwen, E.S., Moore, R.T., Munar, E., Nadal, M., Nawroth, C., Nolte, S., Pelé, M., Potì, P., Rakoczy, H., Riedel, J., Romain, A., Rossano, F., Russell, Y., Sabbatini, G., Schäfer, M., Scheumann, M., Schmelz, M., Schmid, B., Schmitt, V., Sebastián-Enesco, C., Seed, A.M., Suda-King, C., Tauzin, T., Tempelmann, S., Tennie. C., Truppa, V., Uher, J., Vaish, A., van Leeuwen, E.J.C., Visalberghi, E.M., Völter, C.J., Vonau, V., Wascher, C.A.F., Wittig, R.M., Wolf, W., Tomasello, M., Liebal, K., Call, J. and Haun, D.B.M. |
| Abstract | The study of great ape cognition offers insights into the evolutionary origins of human intelligence, but is hindered by small sample sizes and restricted access to data. To address this, we present the EVApeCognition Dataset, a publicly available resource comprising 262 experimental datasets from 150 scientific publications from the Wolfgang Köhler Primate Research Center (2004–2021) in Leipzig, Germany. Eighty-one apes participated in 150 studies, with a majority (N = 78) participating in more than one study. Publication of the dataset aims to make these unique datasets accessible for future meta-analyses and correlational analyses, helping us better understand how our great ape relatives think, learn, and behave. |
| Sustainable Development Goals | 3 Good health and well-being |
| Middlesex University Theme | Health & Wellbeing |
| Publisher | Nature |
| Journal | Scientific Data |
| ISSN | |
| Electronic | 2052-4463 |
| Publication dates | |
| Online | 09 Apr 2026 |
| Publication process dates | |
| Submitted | 13 Nov 2025 |
| Accepted | 31 Mar 2026 |
| Deposited | 18 May 2026 |
| Output status | Published |
| Publisher's version | License File Access Level Open |
| Supplemental file | File Access Level Open |
| Copyright Statement | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Digital Object Identifier (DOI) | https://doi.org/10.1038/s41597-026-07191-6 |
| PubMed ID | 41957049 |
| Language | English |
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| File access level: Open | ||
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