Includes bibliographical references and index.

Multi-species ethnography is a comparatively recent development in the social sciences aimed at attempting to document and analyse interactions between members of different species. Conceptually, as well as methodologically, it has been the subject of much debate. Debate has focused on the logistics of utilising qualitative data collection methods in the study of nonhuman others, the implications of seeing nonhuman others as valid ethnographic subjects, and the validity of classificatory categories such as 'species' when it comes to understanding the lived experiences of the other beings with whom humans interact. In order to produce meaningful multi-species ethnography, researchers need to engage empathetically with the different participants in a social interaction. This empathetic engagement requires researchers to recognise other participants as individuals (where possible) with certain defining characteristics (e.g. four legs, highly developed sense of smell, non-verbal), which shape their participation in and perception of the interaction. The fieldnotes and analysis in this dataset are provided by Dr Samantha Hurn from Exeter University and are drawn from fieldwork she conducted at the Skanda Vale ashram in west Wales, UK. Skanda Vale is a multi-faith, multi-species monastic community. The monks and nuns at Skanda Vale care for a wide variety of animals as part of their practice of seva or karma yoga (selfless action as a form of worship). The notes relate to a series of multi-species interactions between humans and dogs, which Sam observed and experienced while conducting participant observation at the ashram in 2013. Rough fieldnotes were initially written down immediately after the event in a notebook, which Sam carried with her at all times while in the field. They were then expanded an hour later into a detailed account of events, or 'thick description', which was then analysed. This dataset will help you think through the issues associated with conducting and analysing participant observation with nonhuman animals. The dataset will be of most interest to those conducting a multi-species ethnography.

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