Water Analytics and Management with Real-time Linked Dataspaces
13
Fig. 3 Datasets and data sources in the WKAN catalog for the NUIG pilot
level, and where different decisions are taken to manage water on these levels.
Therefore, water awareness dashboards need to be tailored to different needs of
different water usage levels. The data collected by smart water meters is enriched
with contextually Linked Data and processed in real-time; hence, allowing for
deeper data analysis and faster reactions.
• Water consumption: Hydro-meteorological forecasts predict natural demand
and supply of water and can be used to prepare and adjust water supply. Forecasting systems can achieve different goals depending on the level of the system
deployment. At the household level, forecasts include analysis of occupants
behavior and water consumption based on similar historical water usage. These
forecasts can be incorporated into dashboards and used as the drivers for watersaving goal. Forecasting models can further leverage Linked Open Data at the
neighborhood or city-level. At the company-level forecasts similar to those of
the household level are also augmented by models or simulations of the water
needs of subsystems within the organization. Linked Data can be used to perform
benchmarking between similar organizations to identify areas of potential water
optimization.
• Water education: Understanding the impact of a product or service requires
an analysis of all potential water consumption associated with its entire lifecycle. For instance, a water footprint of a product would provide a quantitative
cradle-to-grave analysis of the product/services global water costs (i.e., water
used in raw materials extraction, through materials processing, manufacture,
13
Fig. 3 Datasets and data sources in the WKAN catalog for the NUIG pilot
level, and where different decisions are taken to manage water on these levels.
Therefore, water awareness dashboards need to be tailored to different needs of
different water usage levels. The data collected by smart water meters is enriched
with contextually Linked Data and processed in real-time; hence, allowing for
deeper data analysis and faster reactions.
• Water consumption: Hydro-meteorological forecasts predict natural demand
and supply of water and can be used to prepare and adjust water supply. Forecasting systems can achieve different goals depending on the level of the system
deployment. At the household level, forecasts include analysis of occupants
behavior and water consumption based on similar historical water usage. These
forecasts can be incorporated into dashboards and used as the drivers for watersaving goal. Forecasting models can further leverage Linked Open Data at the
neighborhood or city-level. At the company-level forecasts similar to those of
the household level are also augmented by models or simulations of the water
needs of subsystems within the organization. Linked Data can be used to perform
benchmarking between similar organizations to identify areas of potential water
optimization.
• Water education: Understanding the impact of a product or service requires
an analysis of all potential water consumption associated with its entire lifecycle. For instance, a water footprint of a product would provide a quantitative
cradle-to-grave analysis of the product/services global water costs (i.e., water
used in raw materials extraction, through materials processing, manufacture,