Author(s): Shehabeldeen Abdelfatah; Janelcy Alferes; Pieter Colpaert; Julian Andres Rojas; Piet Seuntjens
Linked Author(s):
Keywords: Circular water; Data interoperability; Linked data
Abstract: The increasing frequency of drought and summer salinization in Belgian canals creates operational risks for industrial water users. We present a modular data transformation framework that harmonizes high-frequency sensor streams, laboratory chemistry, and energy consumption records to enable adaptive source allocation and water reuse. Heterogeneous datasets and sensor feeds are transformed via RML mapping[1], validated with SHACL[2], and published as machine-readable RDF[3]. In addition, Linked Data Event Streams (LDES)[4] provide real-time streaming. The framework integrates cataloging (discoverability), fine-grained access control (security), and standards alignment (W3C vocabularies)[5] to ensure interoperability and governance. A pilot deployment for canal feed optimization (industrial water production) demonstrates how semantic data supports source switching between canal water, cooling discharge, groundwater, and potable supplies while maintaining quality and energy constraints. This approach improves data interoperability, reduces time-to-insight for operational decisions, and demonstrates a scalable blueprint for circular industrial water management.
Year: 2026