Renewable energy decision support systems: The challenge of data integration

Abstract

The practical benefits of a Decision Support System rely heavily on the system's ability to efficiently aggregate and manage large volumes of data, information, and knowledge from heterogeneous sources. The authors approach this challenge and explore the concept of flexible software architectures that support highly customizable decision environments at end-user level. The paper proposes a mechanism applied in the Renewable Energy filed that enables end-users to visually describe data and knowledge source structures using a set of data types and semantic annotations, and to integrate them into the DSS logic without intervention from system developers.