# Protocol to discover machine-readable entities of the ecosystem management actions taxonomy

## TL;DR

This paper introduces a protocol to extract machine-readable data about ecosystem management actions from online sources.

## Contribution

A novel protocol for discovering and learning new EMAT taxa using software-assisted processing of online stories.

## Key findings

- A protocol was developed for acquiring and processing stories to extract EMAT-related actions.
- The method enables the discovery of new EMAT taxa through software-assisted analysis.
- The approach supports data collection for conservation science variables.

## Abstract

The ecosystem management actions taxonomy (EMAT) consists of actions taken by humans and wildlife that affect an ecosystem. Here, I present a protocol for discovering machine-readable entities of the EMAT. I describe steps for acquiring stories from online locations, collecting them into a story file, and processing them through a software package to extract those actions that match EMAT taxa. I then detail procedures for using the story file to learn new EMAT taxa.

•Protocol for the collection of data on the fundamental variables of conservation science•Story acquisition from online locations, story file collection, and processing•Steps for discovering new EMAT taxa using a software-assisted technique

Protocol for the collection of data on the fundamental variables of conservation science

Story acquisition from online locations, story file collection, and processing

Steps for discovering new EMAT taxa using a software-assisted technique

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

The ecosystem management actions taxonomy (EMAT) consists of actions taken by humans and wildlife that affect an ecosystem. Here, I present a protocol for discovering machine-readable entities of the EMAT. I describe steps for acquiring stories from online locations, collecting them into a story file, and processing them through a software package to extract those actions that match EMAT taxa. I then detail procedures for using the story file to learn new EMAT taxa.