Return to Bali

TL;DR

This paper presents the Return to Bali project, which aims to create a comprehensive ethnobotanical dataset of Bali's flora using innovative documentation methods compatible with machine learning, balancing stakeholder interests and ethical considerations.

Contribution

It introduces new methods for documenting underrepresented ethnobotanical knowledge and integrating it with machine learning frameworks.

Findings

Developed a living ethnobotanical dataset of Bali's flora

Proposed practical approaches for ethical knowledge sharing

Enhanced machine learning compatibility for ethnobotanical data

Abstract

This paper gives an overview of the project Return to Bali that seeks to create a living dataset of ethnobotanically significant flora on the island of Bali and new methods through which underrepresented forms of knowledge can be documented, shared and made compatible within the logics of machine learning while considering practical approaches to benefit multiple stakeholders and preventing unintended harm.