Abstract
Water treatment systems face increasing pressure for automation driven by decentralization trends and regulatory requirements, yet deploying the necessary data-driven processes remains difficult due to fragmented data sources, unstructured metadata, and lack of interoperability across facilities. We present WaTr, an ontology designed for water treatment operations that captures fine-grained treatment processes, substance flows, and external references to heterogeneous data sources, and Acquirium, a co-designed data management platform that enables metadata exploration without requiring expertise in semantic query languages. WaTr recasts and significantly extends existing building ontologies to support a wide array of water treatment technologies and concepts. Acquirium supports a novel dataframe-style API for progressive graph query refinement and a lightweight “soft-sensor” abstraction for deploying portable analytics. We demonstrate that Acquirium reduces application code by up to 4 times compared to existing platforms, while scaling to hundreds of concurrent processes and complex soft-sensor compositions with sub-second end-to-end latency. These contributions lower the barrier to developing interoperable, data-driven applications for water treatment facilities.
| Original language | American English |
|---|---|
| Pages | 218-229 |
| Number of pages | 12 |
| DOIs | |
| State | Published - 2026 |
| Event | BuildSys '26: The 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation - Banff, Canada Duration: 22 Jun 2026 → 25 Jun 2026 |
Conference
| Conference | BuildSys '26: The 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation |
|---|---|
| City | Banff, Canada |
| Period | 22/06/26 → 25/06/26 |
NLR Publication Number
- NLR/CP-5700-101908
Keywords
- data management
- knowledge graphs
- ontologies
- RDF
- semantic interoperability
- smart infrastructure
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