<scp>OpenDDF</scp> Advances Knowledge Service‐Oriented Disaster Data Governance

ABSTRACT The integration of multi‐source heterogeneous data, inconsistent metadata standards, and limited knowledge service capabilities remains major challenges in building open science platforms for disaster risk reduction (DRR). This study proposes the Open and Extensible Disaster Data Governance Framework (OpenDDF), an innovative framework designed to enhance FAIR principles (Findable, Accessible, Interoperable, and Reusable) disaster data governance and knowledge services capacity. This framework integrates the development of disaster data classification systems, metadata standards, data management protocols, and online knowledge service modes, encompassing the entire data lifecycle of collection, processing, storage, and sharing. Guided by this framework, the Disaster Risk Reduction Knowledge Service system (DRRKS) has been developed and applied internationally, showcasing DRR data governance technologies and knowledge service contributions. DRRKS established four data types disaster data classification system, adopted 17 metadata and disaster data management standards, and developed four types of data processing and storage workflows. In addition, 25 software functions have been independently developed to support four online knowledge service modes implementation. OpenDDF bridges semantic and procedural gaps between raw disaster data to disaster knowledge data, lays the foundation for next‐generation big data–and artificial intelligence–oriented disaster risk reduction knowledge services.