A Metadata-Driven Architecture for Federated Data Asset Management and Visualization in Energy Monitoring Networks
DOI:
https://doi.org/10.13052/jwe1540-9589.2522Keywords:
Metadata federation, metadata-driven monitoring, web-based system engineering, ontology alignment, distributed energy systems, governance and anomaly detectionAbstract
Distributed energy systems increasingly consist of heterogeneous assets and organizations that must exchange operational data while preserving interoperability, security, and regulatory compliance. Existing integration solutions often rely on syntactic adapters or centralized data hubs, which scale poorly and offer limited transparency or governance. This paper presents a metadata-driven federated monitoring architecture that integrates ontology-based metadata federation, event-driven microservices, and governance-aware provenance tracking to enable secure, scalable, and auditable data sharing across distributed energy infrastructures.
The proposed system models all assets and data streams through a unified semantic graph, aligning heterogeneous schemas via automated ontology matching and combined lexical–structural similarity scoring. A microservices pipeline ingests multi-protocol data (OPC-UA, MQTT, REST), applies stream analytics for anomaly detection, and enforces access and compliance policies at the metadata layer. A Web-based interface allows operators to issue GraphQL queries, visualize distributed assets, and monitor real-time alerts linked to provenance records. A prototype implementation demonstrates operational-scale efficiency, achieving low-latency response (≤540 ms for hybrid metadata–telemetry queries over 10,000 assets), near-linear scalability (∼4.5% CPU growth per added node), and high governance accuracy (precision 0.90, recall 0.95, median detection 1.6 s) while maintaining minimal overhead (<8% added latency). These results highlight that the proposed metadata-driven federation delivers both technical performance and governance reliability unmatched by existing Web-based integration frameworks. These results show that metadata federation can be deployed at operational scale while providing explainable compliance and trustworthy data sharing across organizational boundaries. This research advances the state of the art in Web-based system engineering by combining semantic modeling, distributed processing, and security governance into a single deployable framework. Beyond energy systems, the approach offers a foundation for interoperable and auditable monitoring in other critical cyber-physical domains such as industrial IoT, urban infrastructure, and healthcare telemetry.
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