PRINCIPLES OF GOOD DATA

In recent years, there has been an exponential increase in the collection, aggregation and automated analysis of information by government and private actors that disproportionately disadvantages the underrepresented, marginalized and unheard. In response to this there has been significant critique regarding what could be termed ‘bad’ data practices in the globalised digital economy. Considerations of ‘bad data’ practices often only provide critiques rather than engaging constructively with a new vision of how digital technologies and data can be used productively and justly to promote social, economic, cultural and politically progressive goals. In this paper we consider the fundamentals of Good Data to increase trust. We begin by conceptual considerations of the nature of ‘data’ and ‘goodness’. We align our principles with the Data Information Knowledge Wisdom (DIKW) model and use the term ‘data’ as a proxy for the whole DIKW model. Given the limits of our knowledge of moral facts (should they exist) and in light of colonial and post-colonial data practices we assume a hybrid moral theory—where we allow that some moral facts may be objective (e.g. ‘tolerance’ or ‘openness’) and others relative. We advocate an ethic of active seeking, openness and tolerance to diverse views on ‘the good’ particularly consultation with the underrepresented, marginalised and unheard. We go on to defend fifteen principles of good data under four banners: Community, Rights, Usability & Politics in order to ultimately progress a more just digital economy and society.