The Structure of Indigenous Data

All data may be considered as exhibiting structure at two levels: a ‘micro’ level of constituent elements and relations, and a ‘macro’ level of patterns in the dataset as a whole. Macro-level structure emerges from micro-level structure, via a combination of factors both internal and external to the data itself. When we are dealing with data about people, dataset structure is determined at a macro-level by the interaction of two factors: The lived reality of the people from whom the data is collected, and the research objectives of the people who collect the data. The interaction between these two factors may range between harmony and tension, which in turn generates either self-consistency or contradictions in dataset structure. In colonial administrative settings, because of the competing and asymmetrically resourced interests of Indigenous and colonizing communities, data collection has historically been performed by government, while the people whose lands have been colonized are the ones from whom data is collected. Conflicting interests tend to shift the structure of resulting datasets towards a state of inherent contradiction, generating limited insights. The twin emerging movements of Indigenous data governance, and Indigenous data sovereignty provide an opportunity to engage in large-scale data restructuring initiatives. A new interest on the part of government departments and agencies in facilitating Indigenous governance over data concerning Indigenous peoples, means that there is now an opportunity to reconsider not only the historic skewing of data collection and modelling, but also the ongoing practice of exclusive data structure management by government.