12
Umair et al.
available through the real-time node. Periodically, the streaming data is pushed to
the historical node as new data arrives. The broker node of Druid seamlessly exposes
batch data and real-time data, without the need for writing queries for real-time and
batch data separately.
6.1 Data Sources & Open Data
The pilots in the Waternomics project aim to collect both real-time and historical
data for water management. For instance, the NUIG and CnaC pilots include
following data sources for large buildings.
• Historical and batch data from building management system
• Real-time data from ultrasonic water sensors
A set of relevant open datasets for both pilot sites are included in the Waternomics
catalog:
• Open data from weather prediction and observation services
• Public calendar data used by analytics services for distinguishing between water
consumption in working days and holidays.
• Drought data in Ireland
• Updates from Irish Water services
All of the above-mentioned data sources joined the real-time dataspace for NUIG
and CnaC pilots through definition in the WKAN catalog. Figure 3 shows a list of
datasets for the NUIG pilot. It shows summary meta-data for each dataset in the form
of tags and description. Users can select a data source to reveal further meta-data
which includes the location of data. As a convention, all datasets for historical and
real-time data from sensors of pilots are tagged as private. This way there associated
meta-data is only visible to authorized users. By comparison, open data sets are
defined as public datasets which can be used by everyone.
6.2 Applications
The applications that may be built on top of Waternomics dataspace are diverse;
they include water awareness dashboards, decision support for the different targeted
users (i.e. domestic users, organizations, cities), and water availability/forecasting,
dynamic pricing, and water footprints.
• Water awareness: Low comprehension of water flows by users and over usage is
one of the biggest causes of water wastage. A lack of awareness on the amount of
water consumed leads to the lack of incentives to monitor and affect the situation.
Water awareness requires different information for household, company, and city
Umair et al.
available through the real-time node. Periodically, the streaming data is pushed to
the historical node as new data arrives. The broker node of Druid seamlessly exposes
batch data and real-time data, without the need for writing queries for real-time and
batch data separately.
6.1 Data Sources & Open Data
The pilots in the Waternomics project aim to collect both real-time and historical
data for water management. For instance, the NUIG and CnaC pilots include
following data sources for large buildings.
• Historical and batch data from building management system
• Real-time data from ultrasonic water sensors
A set of relevant open datasets for both pilot sites are included in the Waternomics
catalog:
• Open data from weather prediction and observation services
• Public calendar data used by analytics services for distinguishing between water
consumption in working days and holidays.
• Drought data in Ireland
• Updates from Irish Water services
All of the above-mentioned data sources joined the real-time dataspace for NUIG
and CnaC pilots through definition in the WKAN catalog. Figure 3 shows a list of
datasets for the NUIG pilot. It shows summary meta-data for each dataset in the form
of tags and description. Users can select a data source to reveal further meta-data
which includes the location of data. As a convention, all datasets for historical and
real-time data from sensors of pilots are tagged as private. This way there associated
meta-data is only visible to authorized users. By comparison, open data sets are
defined as public datasets which can be used by everyone.
6.2 Applications
The applications that may be built on top of Waternomics dataspace are diverse;
they include water awareness dashboards, decision support for the different targeted
users (i.e. domestic users, organizations, cities), and water availability/forecasting,
dynamic pricing, and water footprints.
• Water awareness: Low comprehension of water flows by users and over usage is
one of the biggest causes of water wastage. A lack of awareness on the amount of
water consumed leads to the lack of incentives to monitor and affect the situation.
Water awareness requires different information for household, company, and city