The Kaitiaki Intelligence Platform: conceptual foundations for an indigenous environmental sensing network

Area of Science:

• Environmental Science
• Indigenous Studies
• Data Science

Background:

• Māori agribusiness collectives (MACs) and iwi in Aotearoa New Zealand (AoNZ) are increasing their focus on environmental intelligence.
• Advancements in sensing technologies, AI, and data warehousing enable the establishment of Environmental Sensor Networks (ESNs).

Purpose of the Study:

• To examine the environmental data MACs and iwi aim to capture with an ESN.
• To understand their preferences for data structure, querying, and communication.

Main Methods:

• Investigated data types sought by MAC and iwi partners for ESNs.
• Analyzed preferences for data structure, querying, and communication methods.
• Explored the integration of mātauranga (Māori knowledge) with AI and sensing technologies.

Main Results:

• Partners aim to collect diverse biophysical data using remote and in-situ sensing, integrating Place-based intelligence and mātauranga.
• Data structuring using Māori environmental ontologies and AI training with mātauranga are preferred.
• Culturally sensitive data communication via kin-centric metaphors and layered data security for Indigenous data sovereignty are emphasized.

Conclusions:

• The Kaitiaki Intelligence Platform project is designing an Indigenous ESN tailored to MAC and iwi needs.
• This approach supports culturally informed environmental monitoring and upholds Indigenous data sovereignty principles.