Measuring behaviour means assigning numbers to observations of behaviour according to specified rules. Converting a stream of behaviour into behavioural metrics involves choosing and defining specific categories of behaviour that can be measured. Behavioural categories can be described in terms of their physical structure or their consequences. An ethogram is a catalogue of the species-typical behavioural categories displayed by a species in a specified environment. Descriptions of behavioural categories should be unambiguous and written down before data collection starts. Behavioural categories can be designated as either events (short duration) or states (longer duration). Behavioural categories are used to generate metrics such as latencies, frequencies, durations and intensities. Two or more metrics can be combined to form a composite metric. Metrics can be at different levels of measurement, ranging from nominal (weakest) to ratio (strongest).

It has become increasingly apparent that different chimpanzee populations behave differently. Most behaviours and vocalizations are observed across all or most populations. Some behaviours, however, are specific to few populations and different populations behave disparately when solving the same problems. Instead of speaking about the ‘typical’ behaviours, one can probably speak better of a range of chimpanzee behaviours. Between populations, behaviours can range widely. For good comparability and to avoid biases, observers either need to unilaterally use the same protocol or it needs to be apparent how and which data have been collected. Here, we clarify the protocol under which long-term data are collected by the Taï Chimpanzee Project. Despite regular changes to improve and update long-term data collection, our core data collection has remained unchanged, allowing use of the whole data set in analyses. With this chapter, not only can we interpret results generated from the Taï database with more accuracy, but also provide more accessibility for comparisons than currently available. One of the outcomes of this chapter will be making comparisons across study populations easier.