MacaqueNet: Advancing comparative behavioural research through large-scale collaboration

1. There is a vast and ever-accumulating amount of behavioural data on individuallyrecognised animals, an incredible resource to shed light on the ecological andevolutionary drivers of variation in animal behaviour. Yet, the full potential of suchdata lies in comparative research across taxa with distinct life histories and ecolo-gies. Substantial challenges impede systematic comparisons, one of which is thelack of persistent, accessible and standardised databases.2. Big-team approaches to building standardised databases offer a solution to fa-cilitating reliable cross-species comparisons. By sharing both data and expertiseamong researchers, these approaches ensure that valuable data, which mightotherwise go unused, become easier to discover, repurpose and synthesise.Additionally, such large-scale collaborations promote a culture of sharing withinthe research community, incentivising researchers to contribute their data by en-suring their interests are considered through clear sharing guidelines. Active com-munication with the data contributors during the standardisation process alsohelps avoid misinterpretation of the data, ultimately improving the reliability ofcomparative databases.3. Here, we introduce MacaqueNet, a global collaboration of over 100 research -ers (https://macaquenet.github.io/) aimed at unlocking the wealth of cross-species data for research on macaque social behaviour. The MacaqueNetdatabase encompasses data from 1981 to the present on 61 populations across14 species and is the first publicly searchable and standardised database on af-filiative and agonistic animal social behaviour. We describe the establishmentof MacaqueNet, from the steps we took to start a large- scale collective, to thecreation of a cross- species collaborative database and the implementation ofdata entry and retrieval protocols.4. We share MacaqueNet's component resources: an R package for data standardi-sation, website code, the relational database structure, a glossary and data shar-ing terms of use. With all these components openly accessible, MacaqueNet canact as a fully replicable template for future endeavours establishing large-scalecollaborative comparative databases