🤖 AI Summary
This work addresses the loss of semantic metadata—such as node hierarchy and engineering units—when storing OPC UA time-series data in databases, as well as unstable and conflicting node identifiers across sessions from multiple OPC UA servers. To resolve these issues, the authors propose the opcua-ts architecture, which enables, for the first time, the joint persistent storage of semantic metadata alongside time-series telemetry. By leveraging lifecycle-stable connection keys, the system reconstructs the original address space and exposes it as a real-time OPC UA endpoint. Validation through NodeSet2 XML round-trip testing and experiments with a boiler simulator demonstrates that the approach accurately and robustly reconstructs multi-source OPC UA address spaces, effectively mitigating identifier conflicts and session instability.
📝 Abstract
OPC UA has become the dominant open protocol in operational technology. Time-series databases routinely archive OPC UA telemetry but discard the semantic metadata (node hierarchy, engineering units, and type definitions) which gives sensor values their meaning. Recovering this information from a time-series database is non-trivial: namespace indices recorded at the source are session-local and unstable across restarts, and naive merging across multiple source servers results in identifier collisions. We present opcua-ts, an implemented architecture that persists this semantic information alongside its telemetry in a general-purpose time-series database under a lifecycle-stable join key, and that reconstructs the source address space as a live OPC UA endpoint. We characterize the conditions under which the reconstruction is sound across multi-source deployments and validate the approach with a NodeSet2 XML round-trip against the source server. Initial results from a boiler-simulator round-trip indicate that the approach is feasible.