Towards Scalable and Interoperable Geospatial Vector Data Federation via a Decentralized Canonical Metadata-Driven Model

Abstract

In complex and distributed environments, geospatial vector data is vital for planning, analysis, and decision-making. Yet centralized architectures often limit data producers autonomy, create scalability challenges, and hinder seamless sharing across institutional boundaries—particularly in heterogeneous systems with varying metadata standards. Existing spatial infrastructures are largely optimized for both raster and vector data and rely on centralized repositories or tightly coupled systems. These approaches provide limited support for decentralized governance, flexible metadata management, and federated access to vector datasets, which are crucial for autonomy and interoperability. This study introduces a metadata-driven model to federate access to distributed geospatial vector data while preserving contributor sovereignty. The model consists of three layers: 1) Presentation Layer—offers user interface tools for querying and visualizing geospatial data. 2) Semantic Layer—manages a canonical metadata schema replicated across stakeholders via a federated LDAP directory and distributed Directory Information Tree, ensuring consistent yet autonomous governance. 3) Federation Layer—enables remote data retrieval through an access engine, APIs, and GeoJSON formatting without enforcing global standardization. The system supports flexible mappings for non-core metadata fields, avoiding data loss and allowing local customization. This model advances spatial data infrastructures by enabling decentralized, scalable, and interoperable sharing. It reduces reliance on centralized map servers, mitigates synchronization latency, and facilitates conflict resolution across domains. Most importantly, it fosters collaborative environments where producers retain control of their assets while contributing to unified decision-support systems. The model provides a foundation for open, federated platforms in environmental monitoring, urban planning, and smart governance.