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As the global ‘data revolution’ accelerates, how can the data rights and interests of indigenous peoples be secured? Premised on the United Nations Declaration on the Rights of Indigenous Peoples, this book argues that indigenous peoples have inherent and inalienable rights relating to the collection, ownership and application of data about them, and about their lifeways and territories. As the first book to focus on indigenous data sovereignty, it asks: what does data sovereignty mean for indigenous peoples, and how is it being used in their pursuit of self-determination? The varied group of mostly indigenous contributors theorise and conceptualise this fast-emerging field and present case studies that illustrate the challenges and opportunities involved. These range from indigenous communities grappling with issues of identity, governance and development, to national governments and NGOs seeking to formulate a response to indigenous demands for data ownership. While the book is focused on the CANZUS states of Canada, Australia, Aotearoa/New Zealand and the United States, much of the content and discussion will be of interest and practical value to a broader global audience.
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As the global ‘data revolution’ accelerates, how can the data rights and interests of indigenous peoples be secured? Premised on the United Nations Declaration on the Rights of Indigenous Peoples, this book argues that indigenous peoples have inherent and inalienable rights relating to the collection, ownership and application of data about them, and about their lifeways and territories. As the first book to focus on indigenous data sovereignty, it asks: what does data sovereignty mean for indigenous peoples, and how is it being used in their pursuit of self-determination? The varied group of mostly indigenous contributors theorise and conceptualise this fast-emerging field and present case studies that illustrate the challenges and opportunities involved. These range from indigenous communities grappling with issues of identity, governance and development, to national governments and NGOs seeking to formulate a response to indigenous demands for data ownership. While the book is focused on the CANZUS states of Canada, Australia, Aotearoa/New Zealand and the United States, much of the content and discussion will be of interest and practical value to a broader global audience.
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Maori tribal authorities have sought to measure the wellbeing of their people as a baseline for determining the extent to which their economic, social, and cultural goals are being achieved. In recent years, data from government-administered social surveys and/or censuses have become a significant source of information. Using the tribal authority of Te Runanga o Ngai Tahu (TRONT) as a case study, this paper explores and compares data concerning Ngai Tahu wellbeing contained in two recently completed TRONT reports: the Ngai Tahu State of the Nation 2015 report (a quantitative study derived from government-administered survey data); and, the preliminary findings from the Ngai Tahu Whenua Project (a qualitative study undertaken by TRONT). Both studies present similar results regarding levels of tribal economic wellbeing, however, they show different results in regards to levels of cultural wellbeing. The qualitative study reveals reasonably high levels of cultural engagement among participants. Conversely, the quantitative study demonstrates reasonably low levels of cultural engagement. The difference is explained in each study's approach to understanding culture. The quantitative study viewed culture as engagement in 'static' cultural practices, whereas the qualitative study viewed Maori culture as a 'lived' set of deep networks and connections between individuals, their whanau (extended family), and places of symbolic cultural importance (particularly land and water). It is argued that measuring 'lived' culture would provide a better means of ascertaining cultural wellbeing. It is suggested that a useful means of measuring Maori lived culture would be to determine the quality and depth of relational networks.