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