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Indigenous Data Network National Survey: Indigenous-Controlled
Research Organizations
Indigenous Studies UnitMelbourne School of Population & Global Health
data-indigenous@unimelb.edu.au
IDN
©Indigenous Data Network, University of Melbourne
©Indigenous Data Network, University of Melbourne
The project in a nutshell: The Indigenous Data Network
©Indigenous Data Network, University of Melbourne
The project in a nutshell: National Survey of Indigenous-Controlled Research Organization
48,000 Constituents
216,000 Constituents
34,000 Constituents
2,400 Constituents
APY
14,300 Constituents
48,000 Constituents
362,600 Constituents Total
Key issues: Colonization => Appropriation => Data Anxiety
©Indigenous Data Network, University of Melbourne
Lessons Learnt: Effective Governance ≡ Self Governance
©Indigenous Data Network, University of Melbourne
1. Building or sustaining community ownership of a collection
Building a sustainable ownership framework in the Indigenous community-controlled data sector requires a robust and transparent system of protections designed and administered by the sector itself.
2. Content strategy for transformative collection
A successful content strategy based on a common governance framework can be achieved by orienting the sector towards leading international standards: (a) Five Safes + (b) FAIR Guiding Principles + (c) EU General Data Protection Regulation.
3. Data standardisation in a transformative data collection
The primary threshold for data structure and formatting standardization across the sector is a common independent FORUM for coordinating governance, training and technical cooperation.
4. Models of institutional participation for a more sustainable national and community collection
The distinctions between data ownership, custodianship and stewardship are key instruments in resolving underlying tensions. This language is not yet developed.
Acknowledgements
©Indigenous Data Network, University of Melbourne
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