Beyond the horizon: immersive developments for animal ecology research

Area of Science:

• Ecology
• Computer Science
• Data Science

Background:

• The increasing volume of animal ecology data presents analytical challenges and opportunities.
• Interdisciplinary collaboration between ecologists and computer scientists is crucial for advancing research.
• Emerging immersive technologies offer new avenues for data analysis and interpretation.

Purpose of the Study:

• To highlight the potential of interdisciplinary research between animal ecology and computer science.
• To introduce Immersive Analytics (IA) as a novel approach for analyzing ecological data.
• To propose a collaborative framework for developing IA in animal ecology.

Main Methods:

• Literature review and conceptual framework development.
• Discussion of challenges and opportunities in applying IA to animal ecology.
• Proposal for a structured, interdisciplinary approach.

Main Results:

• Identification of a significant opportunity for integrating IA into animal ecology research.
• Outlined potential benefits including reduced analysis effort and broader research scope.
• Defined key areas for collaboration: research agenda, design space, software frameworks, and guidelines.

Conclusions:

• A joint effort between biologists and computer scientists can establish IA foundations in animal ecology.
• This collaboration can lead to improved data analysis, comparability, and a more holistic understanding of animal ecology.
• The proposed approach aims to create practical guidelines and robust software for IA in ecological research.