ABSTRACT
The language used to describe the process by which we get data might suggest otherwise. The term ‘raw data’ is still commonly used. Although it has its value in distinguishing the primary data used in a project from secondary refined forms, it conveys an unfortunate impression of data as winnable commodities like potatoes in a field or iron ore fresh from the mine. The familiar terms ‘data gathering’ and ‘data collection’ also create an image of the scientist harvesting natural products, basket in hand. It is a long time since most scientists were comfortable with the image of themselves as empirical searchers for nuggets of revealed truth, and there have naturally been attempts to find alternative terms. Among social scientists, often much more directly conscious of the role of language than geographers, several alternatives have been suggested. The terms ‘data making’, ‘data production’, and ‘data construction’ have all had their advocates (Bateson 1984: 5, Sayer 1992: 272n). They have also had their critics, since they all suggest an element of conscious manufacture which runs contrary to the accepted ideal of the scientist as a transparent medium through which the truth is elucidated, and at the worst imply downright falsification.2 ‘Data generation’ is perhaps the best choice from a poor field, on the one hand avoiding the danger of suggesting that data are raw natural products, and on the other not over-emphasising the element of manufacture.
