RA2: Indigenous Data in Systems
Recognition of indigenous data in Māori data classification schema and Indigenous data provenance standard and the valuation of Māori data resources.
RA 2 Summit Recordings
Watch keynotes from our researchers
Recent work in Indigenous and Māori data sovereignty has highlighted an urgent need for data schemas, methods and tools that can be applied to Indigenous data a range of real-world domains at different scales. Our programme has developed novel approaches to data classification, provenance, and valuation to enable greater transparency and control of Indigenous data.
Our team
- Maui Hudson, Te Kotahi Research Institute
- Sebastian Link, University of Auckland
- Jane Anderson, New York University
- John Deck, UC Berkeley
- Tim Coltman, University of Waikato
- Jason Mika, University of Waikato
- KatieLee Riddle, Te Kotahi Research Institute
- Jacob Golan, New York University
- Natalie Kusabs, University of Waikato
Research outputs
- Eng, K. (2025) Machine Learning Meets Real-World Data: Harmful Algal Bloom Prediction in Practice. [Master's Dissertation, Summary, University of Waikato].
- Coltman, T., Hudson, M., Mika, J., Matthews, Y., Anderson, J., Kusabs, N., Riddle, KL., Golan, J. Benefit sharing on genetic resources: Modelling data access, control and willingness-to-pay for digital sequence information. British Ecological Society. https://doi.org/10.1002/2688-8319.70063
- Stonier, J., Woodman, L., Alshammari, M., Baxter, K., Giovanni Busetto, A., Cummings, R., Nighat, D., Garg, A., Hsiao, K., Hudson M., Kanamugire, D., Kapoor, A., Lei, Z., Paz Canales Loebel, M., Lu, J., Oduor Lungati, A., Mizouni, E., Jeet Singh, P., Telford, S., Ulrich, G. (2024). Advancing Data Equity: An Action-Oriented Framework. World Economic Forum. Retrieved from World Economic Forum.
- Anderson J., Hudson. M., RunningHawk. S., & Riddle., K.L. (2024) Recognizing Indigenous Interests: Labeling DSI with Provenance Metadata. Policy Brief. ENRICH.
- O’Brien, M., Duerr, R., Taitingfong, R., Martinez, A., Vera, L., Jennings, L., Downs, R., Antognoli, E., ten Brink, T., Halmai, N., Carroll, S., David-Chavez, D., Hudson, M., & Buttigieg, P. (2024) Earth Science Data Repositories: Implementing the CARE Principles. Data Science Journal, 23: 37, pp. 1–29. https://doi.org/10.5334/dsj-2024-037
- Taitingfong, R., Martinez, A., Russo Carroll, S., Hudson, M., & Anderson, J. (2023). Indigenous Metadata Bundle Communiqué. Collaboratory for Indigenous Data Governance, ENRICH: Equity for Indigenous Research and Innovation Coordinating Hub, and Tikanga in Technology. DOI: 10.6084/m9.figshare.24353743
- Hudson, M., Carroll, SR., Anderson, J., Blackwater, D., Cordova-Marks, FM., Cummins, J., David-Chavez, D., Fernandez, A., Garba, I., Hiraldo, D., Jäger, MB., Jennings, LL., Martinez, A., Sterling, R., Walker, JD., & Rowe, RK. (May 2023). Indigenous Peoples’ Rights in Data: a contribution toward Indigenous Research Sovereignty. Frontiers in Research Metrics Analytics. 8:1173805. https://doi.org/10.3389/frma.2023.1173805
- Golan, J., Riddle, K., Hudson, M., Anderson, J., Kusabs, N., & Coltman, T. (2022, August 30). Benefit sharing: Why inclusive provenance metadata matter. Frontiers. https://doi.org/10.3389/fgene.2022.1014044.
- Jianzheng, L. (2022). Creating an Ontology for Indigenous Data Sovereignty. [Master's Dissertation, University of Auckland].
- Yuhang, L. (2022). Automated Recommendation of Māori Subject Headings for Library Resources. [Master's Dissertation, University of Auckland].
- Yang, Y. (2022). Neo4j Approach in Nga Upoko Tukutuku/Maori Subject Heading. [Master's Dissertation, University of Auckland].
- Wang, C. (2022). SPARQLing Access to Māori Perspectives of Library Data. [Master's Dissertation, University of Auckland].
- Hudson, M. (2021). Indigenous data sovereignty: Towards an equitable and inclusive digital future [Interview]. Just Net Coalition & IT for Change. Retrieved from IT for Change.
- Anderson J., Hudson M. (2020). The Biocultural Labels Initiative: Supporting Indigenous rights in data derived from genetic resources. Biodiversity Information Science and Standards 4: e59230. https://doi.org/10.3897/biss.4.59230