Abstract

This paper is intended to contribute to the discussion of the differential level of adoption of Big Data among research communities. Recognising the impracticality of conducting an audit across all forms and uses of Big Data, we have restricted our enquiry to one very specific form of Big Data, namely general purpose taxonomies, of which Mosaic, Acorn and Origins are examples, that rely on data from a variety of Big Data feeds. The intention of these taxonomies is to enable the records of consumers and citizens held on Big Data datasets to be coded according to type of residential neighbourhood or ethno-cultural heritage without any use of questionnaires. Based on our respective experience in the academic social sciences, in government and in the design and marketing of these taxonomies, we identify the features of these classifications which appear to render them attractive or problematic to different categories of potential user or researcher depending on how the relationship is conceived. We conclude by identifying seven classifications of user or potential user who, on account of their background, current position and future career expectations, tend to respond in different ways to the opportunity to adopt these generic systems as aids for understanding social processes.