A global biodiversity use data infrastructure acknowledging indigenous and local knowledge

Area of Science:

• Biodiversity science
• Data infrastructure
• Indigenous knowledge systems

Background:

• Global biodiversity datasets often exclude or misrepresent knowledge from Indigenous Peoples, Local Communities, and Afro-Descendants (IPLCAD).
• This exclusion leads to data gaps and perpetuates historical inequities in biodiversity governance.
• There is a need for inclusive frameworks that recognize and integrate diverse knowledge systems.

Purpose of the Study:

• To propose minimum data and metadata standards for a global biodiversity knowledge and use data infrastructure.
• To ensure the ethical and traceable use of IPLCAD knowledge within this infrastructure.
• To foster inclusive biodiversity governance by integrating ancestral and academic sciences.

Main Methods:

• Co-designing data and metadata standards with IPLCAD representatives.
• Developing protocols for community attribution and informed consent.
• Establishing a framework for integrating diverse knowledge systems.

Main Results:

• Proposed minimum data and metadata standards tailored for IPLCAD knowledge.
• A framework for ensuring data traceability and ethical use, respecting community rights.
• An integrated approach combining ancestral and academic scientific knowledge.

Conclusions:

• Implementing these standards can rectify historical inequities in biodiversity data.
• This initiative advances global sustainability through inclusive biodiversity governance.
• Co-designed data infrastructure is crucial for equitable and effective biodiversity management.