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In this paper we propose an ontological OLAP (on-line analytical processing) framework to integrate distributed energy sensor data. The OLAP data cube in the framework annotated with semantics with other supporting mechanisms can deal with the issues of the schema inconsistency that may result from integration of heterogeneous data sources. The proposed approach provides a way of storing, reusing and composing OLAP cubes in order to increase system usability. A prototype of the proposed framework based on a number of existing tools such as protégé, Jess, and Fuzzy J has been developed to demonstrate its feasibility. AUTHORSNazaraf Shah has received PhD in multi-agent systems from Coventry University, UK. He is a senior lecturer at the Department of Computing and the Digital Environment, Coventry University, UK. He has to his credit more than 25 publications in the area of multi-agent systems and agent-based simulation. His main research interests are multi-agent systems and service-oriented computing. He has to his credit more than 50 publications concerning knowledge-based systems, distributed database systems, object-oriented database systems, query processing, deductive databases, knowledge-based distributed information systems, multimedia information systems, knowledge-managed computer-assisted instruction systems.

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This paper presented an analytical tool, based on the cost-benefit analysis instrument, intended to be used to estimate both the financial and economic impacts related to the implementation of policy actions and/or projects (interventions) in the field of energy efficiency. The proposed guidelines are intended to provide relevant information and guidance on why and how to conduct financial and economic assessment to a relatively large number of institutions involved in the preparation and appraisal of energy efficiency actions.