Semantic Meta Model for the Description of Resource and Energy Data in the Energy Data Management Cycle
Energy efficiency is a critical competitive factor. Transparency of energy consumption is the key for increasing efficiency of production. For this purpose, existing energy data management systems collect data such as power, gas or water consumption on field level, save them in databases, and aggregate them in reports. However, the identification of saving potentials and the definition of efficiency measures is carried out by energy experts and thus is dependent on a person’s knowledge. The documentation of knowledge about saving potentials and measures does not take place and relations among data and knowledge of various domains are not captured. In this paper, we provide an approach that allows the holistic capture and description of data and knowledge relations. Through the use of an ontology-based meta model, consumption data can be augmented with information about time and place of capture, data type, intended purpose and permissions, as well as interfaces to other systems and relations to knowledge elements. The semantic model is to capture relevant requirements of all information demanders within the energy data management cycle. Therefore, the model is capable of detecting efficiency deficits and retrieving relevant energy efficiency measures within a knowledge base. Thus, energy consumption data can be efficiently used and knowledge about efficiency can be sustainably preserved.
Jörg Franke, Sven Kreitlein, Gunther Reinhart, Christian Gebbe, Rolf Steinhilper and Johannes Böhner
M. Brandmeier et al., "Semantic Meta Model for the Description of Resource and Energy Data in the Energy Data Management Cycle", Applied Mechanics and Materials, Vol. 871, pp. 69-76, 2017