Project

WaterFRAME – Water Fit for Reuse digital Architecture and Modeling Ecosystem

Code
S001124N
Duration
01 October 2023 → 30 September 2027
Funding
Research Foundation - Flanders (FWO)
Research disciplines
  • Natural sciences
    • Knowledge representation and reasoning
    • Decision support and group support systems
  • Engineering and technology
    • Water resources management
    • (Waste)water treatment processes
    • Environmental engineering modelling
Keywords
Water Fit for Reuse
 
Project description

Flanders together with many other regions in Europa has suffered through one of its driest summers in history and this will unfortunately not be a singular event. To ensure sufficient water availability for all actors in the Flemish region (drinking water, agriculture, industry…), we need to significantly increase the resilience of our water management through optimization of existing infrastructures, stimulation of circular water practices and strategic investments in new infrastructure. However, water management is inherently a very complex subject touching many different actors and covering a large spatial scale. Building water resilience thus requires a decision making tool which is able to incorporate this complexity in order to support holistic decisions that can balance multiple objectives. However, bringing available data and modelling tools together over different scales and application domains to address high level technological or societal challenges is not
possible with tools that are currently available. This project will use methodologies based on semantic web standards. More specifically, data standards, a ontology model and a dynamic knowledge graph will be developed as a way to encode and structure knowledge and as such create a standardized and holistic structure of
the water domain. The knowledge graph will be dynamic so it can be continuously populated with new data (sensor data, design data, simulation data) and integration of predictive models and optimization algorithms will be foreseen within its structure allowing for the analysis of holistic scenarios to support decision making. Knowledge graphs can be built in a modular way creating a lot of flexibility for future developments/updates. Since they are based on standardized web
semantics they can be easily queried (used to answer questions). Moreover their standardized form also allows coupling to other sectors (such as energy) for cross-domain decision making.