3 Shifts / Accelerate
Accelerate Innovation

Build Planetary Digital Twin

Prioritize innovations to measure, monitor and model the health of the planet’s biosphere and interactions with economic and social systems.

Summary

Digital twins combined with AI have the capability to conduct automated monitoring of risks and threats to key protected areas (either natural or cultural areas under global protection frameworks), ecosystem services or endangered species. Digital twins can also assist in understanding options and trade offs for achieving different SDGs and MEAs. This can benefit not only national governments, but also private sector companies, research institutions, non-profit organizations, and local communities.

However, many efforts continue to be fragmented and unable to connect in order to monitor planetary health in real time. Major investments are needed to build interoperable digital twins of the earth and its various subsystems that can allow us to monitor and model complex relationships among environmental, social, and economic systems using the best science and data available as well as robust data-protection rules. First, investments to improve the sensing, connectivity and computational requirements for collecting and processing the vast volumes of data, especially for real-time data processing scenarios at a planetary scale.

Second, adoption of transparency principles, data standards and safeguards, Open APIs (Application Programming Interface) and communication protocols that enable safety, privacy, interoperability, transferability, and quality control of key sustainability data across disparate systems. Third, ways to support, and integrate validated citizen science contributions and observations as well as other open-source tools and algorithms into the digital twin ecosystems. Finally, development of applications that enable real-time ingestion and processing of data from the digital twin ecosystem into governments, science, civil society, and private sector ecosystems and vice-versa to inform meaningful forms of analysis and decision support systems.