Delphine De Moor Delphine De Moor Macaela Skelton Macaela Skelton MacaqueNet Federica Amici Federica Amici Malgorzata E. Arlet Malgorzata E. Arlet Krishna N. Balasubramaniam Krishna N. Balasubramaniam Sebastien Ballesta Sebastien Ballesta Andreas Berghänel Andreas Berghänel Carol M. Berman Carol M. Berman Sofia K. Bernstein Sofia K. Bernstein Debottam Bhattacharjee Debottam Bhattacharjee Eliza Bliss-Moreau Eliza Bliss-Moreau Fany Brotcorne Fany Brotcorne Marina Butovskaya Marina Butovskaya Liz A. D. Campbell Liz A. D. Campbell Monica Carosi Monica Carosi Mayukh Chatterjee Mayukh Chatterjee Matthew A. Cooper Matthew A. Cooper Veronica B. Cowl Veronica B. Cowl Claudio De la O Claudio De la O Arianna De Marco Arianna De Marco Amanda M. Dettmer Amanda M. Dettmer Ashni K. Dhawale Ashni K. Dhawale Joseph J. Erinjery Joseph J. Erinjery Cara L. Evans Cara L. Evans Julia Fischer Julia Fischer Iván García-Nisa Iván García-Nisa Gwennan Giraud Gwennan Giraud Roy Hammer Roy Hammer Malene F. Hansen Malene F. Hansen Anna Holzner Anna Holzner Stefano Kaburu Stefano Kaburu Martina Konecna Martina Konecna Honnavalli N. Kumara Honnavalli N. Kumara Marine Larrivaz Marine Larrivaz Jean-Baptiste Leca Jean-Baptiste Leca Mathieu Legrand Mathieu Legrand Julia Lehmann Julia Lehmann Jin-Hua Li Jin-Hua Li Anne-Sophie Lezé Anne-Sophie Lezé Andrew Mac Intosh Andrew Mac Intosh Bonaventura Majolo Bonaventura Majolo Laëtitia Maréchal Laëtitia Maréchal Pascal R. Marty Pascal R. Marty Jorg J. M. Massen Jorg J. M. Massen Risma Illa Maulany Risma Illa Maulany Brenda Mc Cowan Brenda Mc Cowan Richard Mc Farland Richard Mc Farland Pierre Merieau Pierre Merieau Hélène Meunier Hélène Meunier Jérôme Micheletta Jérôme Micheletta Partha S. Mishra Partha S. Mishra Shahrul A M Sah Shahrul A M Sah Sandra Molesti Sandra Molesti Kristen S. Morrow Kristen S. Morrow Nadine Müller-Klein Nadine Müller-Klein Putu Oka Ngakan Putu Oka Ngakan Elisabetta Palagi Elisabetta Palagi Odile Petit Odile Petit Lena S. Pflüger Lena S. Pflüger Eugenia Polizzi di Sorrentino Eugenia Polizzi di Sorrentino Roopali Raghaven Roopali Raghaven Gaël Raimbault Gaël Raimbault Sunita Ram Sunita Ram Ulrich H. Reichard Ulrich H. Reichard Erin P. Riley Erin P. Riley Alan V. Rincon Alan V. Rincon Nadine Ruppert Nadine Ruppert Baptiste Sadoughi Baptiste Sadoughi Kumar Santhosh Kumar Santhosh Gabriele Schino Gabriele Schino Lori K. Sheeran Lori K. Sheeran Joan B. Silk Joan B. Silk Mewa Singh Mewa Singh Anindya Sinha Anindya Sinha Sebastian Sosa Sebastian Sosa Mathieu S Stribos Mathieu S Stribos Cédric Sueur Cédric Sueur Barbara Tiddi Barbara Tiddi Patrick J. Tkaczynski Patrick J. Tkaczynski Florian Trebouet Florian Trebouet Anja Widdig Anja Widdig Jamie Whitehouse Jamie Whitehouse Lauren J. Wooddell Lauren J. Wooddell Dong-Po Xia Dong-Po Xia Lorenzo von Fersen Lorenzo von Fersen Christopher Young Christopher Young Oliver Schülke Oliver Schülke Julia Ostner Julia Ostner Christof Neumann Christof Neumann Julie Duboscq Julie Duboscq Lauren J. N. Brent Lauren J. N. Brent Wiley 2025 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. PDFDocument eng 2025-04-16T08:42:01.294655Z 2025 Animals Behavioral Research Methods Macaca Physiology Behavior, Animal Databases, Factual Social Behavior 6970694 b application/pdf http://creativecommons.org/licenses/by/4.0/