The primary aim of this paper is to investigate and propose a generic framework to integrate Water Supply Distribution Systems using interoperable standards. Information in the water supply chain can be collected by in-situ observations,... more
The primary aim of this paper is to investigate and propose a generic framework to integrate Water Supply Distribution
Systems using interoperable standards. Information in the water supply chain can be collected by in-situ observations,
by reuse of existing geospatial data and by remote sensors. Regardless the information availability, it requires an effort
to integrate this data from different resources because of the heterogeneity between systems and data. The information
consumes time to be analyzed and manipulated in order to make effective decisions. For example, information analysis
to generate proper decisions which can support the match of water supply with water demand while minimizing the
energy consumption. Today water supply distribution managers in Europe use separate tools to gather data from many
distributed resources and to use this data in decision making. All these tools use different ways of communication and
are not connected. To overcome this problem it is required to integrate these tools and systems in a platform where they
can exchange information such that managers can make better decisions. The proposed framework in this research will
allow organizations in water industry to integrate data to accomplish decisional tasks overcoming drawbacks presented
by current interoperability approaches taken elsewhere such as CUAHSI. The architecture of this framework is generic
so that no matter what form client’s data is in, it will be processed and integrated with other clients’ data. For example,
the data can be in the form of Excel files, database or a web service. The integration manager of the architecture will
process the data and transform it into the form to bring consistency such as a web service or documents that use
standards, i.e. WaterML 2.0. To overcome data and systems heterogeneity ontological mechanisms will be used in this
framework. This framework will provide efficient means to analyze information and manipulate data to perform decision
making tasks with decreasing overhead delays. The first contribution of this paper in water industry is the use of the WaterML
2.0 standard. Then, a methodology of a generic framework for integration of water data is proposed.
Systems using interoperable standards. Information in the water supply chain can be collected by in-situ observations,
by reuse of existing geospatial data and by remote sensors. Regardless the information availability, it requires an effort
to integrate this data from different resources because of the heterogeneity between systems and data. The information
consumes time to be analyzed and manipulated in order to make effective decisions. For example, information analysis
to generate proper decisions which can support the match of water supply with water demand while minimizing the
energy consumption. Today water supply distribution managers in Europe use separate tools to gather data from many
distributed resources and to use this data in decision making. All these tools use different ways of communication and
are not connected. To overcome this problem it is required to integrate these tools and systems in a platform where they
can exchange information such that managers can make better decisions. The proposed framework in this research will
allow organizations in water industry to integrate data to accomplish decisional tasks overcoming drawbacks presented
by current interoperability approaches taken elsewhere such as CUAHSI. The architecture of this framework is generic
so that no matter what form client’s data is in, it will be processed and integrated with other clients’ data. For example,
the data can be in the form of Excel files, database or a web service. The integration manager of the architecture will
process the data and transform it into the form to bring consistency such as a web service or documents that use
standards, i.e. WaterML 2.0. To overcome data and systems heterogeneity ontological mechanisms will be used in this
framework. This framework will provide efficient means to analyze information and manipulate data to perform decision
making tasks with decreasing overhead delays. The first contribution of this paper in water industry is the use of the WaterML
2.0 standard. Then, a methodology of a generic framework for integration of water data is proposed.
