Journal of Animal Ecology Wiley Text journal article Testo Articolo di rivista Animals Behavioral Research Methods Macaca Physiology Behavior, Animal Databases, Factual Social Behavior Delphine De Moor Macaela Skelton MacaqueNet Federica Amici Malgorzata E. Arlet Krishna N. Balasubramaniam Sebastien Ballesta Andreas Berghänel Carol M. Berman Sofia K. Bernstein Debottam Bhattacharjee Eliza Bliss-Moreau Fany Brotcorne Marina Butovskaya Liz A. D. Campbell Monica Carosi Mayukh Chatterjee Matthew A. Cooper Veronica B. Cowl Claudio De la O Arianna De Marco Amanda M. Dettmer Ashni K. Dhawale Joseph J. Erinjery Cara L. Evans Julia Fischer Iván García-Nisa Gwennan Giraud Roy Hammer Malene F. Hansen Anna Holzner Stefano Kaburu Martina Konecna Honnavalli N. Kumara Marine Larrivaz Jean-Baptiste Leca Mathieu Legrand Julia Lehmann Jin-Hua Li Anne-Sophie Lezé Andrew Mac Intosh Bonaventura Majolo Laëtitia Maréchal Pascal R. Marty Jorg J. M. Massen Risma Illa Maulany Brenda Mc Cowan Richard Mc Farland Pierre Merieau Hélène Meunier Jérôme Micheletta Partha S. Mishra Shahrul A M Sah Sandra Molesti Kristen S. Morrow Nadine Müller-Klein Putu Oka Ngakan Elisabetta Palagi Odile Petit Lena S. Pflüger Eugenia Polizzi di Sorrentino Roopali Raghaven Gaël Raimbault Sunita Ram Ulrich H. Reichard Erin P. Riley Alan V. Rincon Nadine Ruppert Baptiste Sadoughi Kumar Santhosh Gabriele Schino Lori K. Sheeran Joan B. Silk Mewa Singh Anindya Sinha Sebastian Sosa Mathieu S Stribos Cédric Sueur Barbara Tiddi Patrick J. Tkaczynski Florian Trebouet Anja Widdig Jamie Whitehouse Lauren J. Wooddell Dong-Po Xia Lorenzo von Fersen Christopher Young Oliver Schülke Julia Ostner Christof Neumann Julie Duboscq Lauren J. N. Brent http://creativecommons.org/licenses/by/4.0/ 2025 Text Wissenschaftlicher Artikel application/pdf MacaqueNet: Advancing comparative behavioural research through large-scale collaboration © 2025 The Author(s) open access There is a vast and ever-accumulating amount of behavioural data on individually recognised animals, an incredible resource to shed light on the ecological and evolutionary drivers of variation in animal behaviour. Yet, the full potential of such data lies in comparative research across taxa with distinct life histories and ecologies. Substantial challenges impede systematic comparisons, one of which is the lack of persistent, accessible and standardised databases. Big-team approaches to building standardised databases offer a solution to facilitating reliable cross-species comparisons. By sharing both data and expertise among researchers, these approaches ensure that valuable data, which might otherwise go unused, become easier to discover, repurpose and synthesise. Additionally, such large-scale collaborations promote a culture of sharing within the research community, incentivising researchers to contribute their data by ensuring their interests are considered through clear sharing guidelines. Active communication with the data contributors during the standardisation process also helps avoid misinterpretation of the data, ultimately improving the reliability of comparative databases. Here, we introduce MacaqueNet, a global collaboration of over 100 researchers (https://macaquenet.github.io/) aimed at unlocking the wealth of cross-species data for research on macaque social behaviour. The MacaqueNet database encompasses data from 1981 to the present on 61 populations across 14 species and is the first publicly searchable and standardised database on affiliative and agonistic animal social behaviour. We describe the establishment of MacaqueNet, from the steps we took to start a large-scale collective, to the creation of a cross-species collaborative database and the implementation of data entry and retrieval protocols. We share MacaqueNet's component resources: an R package for data standardisation, website code, the relational database structure, a glossary and data sharing terms of use. With all these components openly accessible, MacaqueNet can act as a fully replicable template for future endeavours establishing large-scale collaborative comparative databases. doi:10.1111/1365-2656.14223 eng https://phaidra.vetmeduni.ac.at/o:4056