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Sensitivity Warning

First Peoples

Aboriginal and Torres Strait Islander peoples should be aware that this resource may contain images or names of people who have since passed away.

Attachment Size
Good data 24.72 MB

This edited collection features 20 chapters by academics, researchers, consultants, scientists and commentators from a range of disciplines and geographic areas. 

Moving away from the strong body of critique of pervasive ‘bad data’ practices by both governments and private actors in the globalized digital economy, this book aims to paint an alternative, more optimistic but still pragmatic picture of the datafied future. The authors examine and propose ‘good data’ practices, values and principles from an interdisciplinary, international perspective. From ideas of data sovereignty and justice, to manifestos for change and calls for activism, this collection opens a multifaceted conversation on the kinds of futures we want to see, and presents concrete steps on how we can start realizing good data in practice.

Key Findings:

  • Good Data Practices for Indigenous Data Sovereignty and Governance - Page 26
    The Indigenous Data Severeignty movement has emerged in response to poor data practices, from the conceptualisation of data items through to reporting of data about Indigenous peoples. This chapter aims to provide clarity concerning the definitions of IDS and IDG; provide an overview of the historical context in which IDS has emerged; and provide examples of IDS and IDG across the spectrum of community, policy and practice.
  • 'Data sovereignty' is the management of information in a way that aligns with the laws, practices and customs of a nation-state in which it is located.5 In the Indigenous context this may manifest at the group (iwi(tribe)/mob/Maori) levels.
  • Trade-offs in Algoritmic Risk Assessment: An Australian Domestic Violence Case Study - Page 96
    The focus for this section is predicting domestic violence recidivism using administrative data. In the context of domestic violence recidivism, national and state-based agencies have begun to develop and implement computerized decision support systems (DSS) and risk assessment tools that draw on standardized data (within and/or across agencies) to help understand the risk of domestic violence recidivism for sub-groups within the population.
  • Recent studies suggest that domestic violence-related risk assessment tools can be effective, particularly to assist under-resourced front-line agencies to make informed and speedy decisions about detention, bail and victim assistance.There is increasing interest in evidence-based crime and social welfare governance that draw on data science and big data, perhaps due to a perception that these kinds of DSS and risk assessment tools are more efficient, objective and less costly than existing approaches.
  • Good Data as Open and Shared Data - Page 173
    Covering topics such as the data journalism and the ethics of the open source, governance of communal data sharing, and the open data index as participatory device.
  • Good Data and Research
  • Smart cities and homes.
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Theory on Demand #29