Abstract

This paper presents a qualitative transformation in the production of official environmental statistics through an ontological data governance framework, applied to Egypt’s Central Agency for Public Mobilization and Statistics (CAPMAS). Adopting a Data Ecosystem Perspective, the study addresses the structural limitations of isolated datasets that hinder the monitoring of complex global challenges such as climate change and climate-induced migration.

The research examines the creation of "semantic bridges" and knowledge graphs linking heterogeneous datasets from multiple ministries. By transforming fragmented administrative records into Linked Open Data (LOD), the framework ensures full alignment with international standards, including FDES 2013 and SEEA.

Results demonstrate that ontological modeling has:

Enhanced Technical Interoperability: Seamlessly integrating administrative records with survey data, ensuring data consistency and automated validation across the statistical system.

Improved Data Trustworthiness: Establishing a unified metadata layer that enhances the transparency and quality of multi-sectoral indicators.

Policy-Ready Insights: Providing accurate indicators connecting environmental degradation to migration patterns, directly supporting evidence-based decision-making.

Strengthened National Data Sovereignty: Building a flexible, future-proof statistical infrastructure aligned with the Sustainable Development Goals (SDGs).

The paper offers practical guidance for National Statistical Offices (NSOs) on overcoming institutional silos and building technical capacity in semantic data science. Egypt’s experience is presented as a replicable model for modernizing national statistical systems into connected, interoperable, and trustworthy data ecosystems.