CERISE - Combining energy and spatial information standards as enabler for smart grids - TKI smart grid project: TKISG01010 - D4.1 Semantic mappings to harmonize energy, geo and government-related information models. Work package 40

Version 1.0 - Final The CERISE-SG project (Combining Energy and Geo information standards as enabler for Smart Grids) focuses on interoperability with a special interest in the information exchanges between smart grids and their surroundings. We hereby focus on the exchange of information to and from smart grids, the government domain and the geo domain. Within the fast changing smart grid world acquiring reliable information from different sources is invaluable. The information required comes from different sources that all use their own (often different) definitions for the data they control. The national registration of buildings for instance contains different data with different definitions from the data source of energy consumption. To exchange information between these sources connections need to be made between the different areas that make sure that correct and reliable data is available. In this document we describe a process to define these mappings. First an identification of the playing field of smart grids is given and the three major domains that are involved are described i.e. (1) the utilities domain, (2) the geographic domain; and (3) the government domain. Because there are already many standardisation processing running within each domain, with different set-ups the cross domain harmonization is extra challenging. In this document we work out two solutions to the harmonization problems: - Define relationships between elements from different models - Express model elements from different models in a common model In this document we propose 'linked data' and semantic web technology as a solution for this challenge, we explain Linked Data and explain how Linked Data can be used to semantically map data models to each other. By actively harmonizing a collection of datasets that are relevant for the smart grid we prove the viability for using 'linked data' as a solution for interoperability challenges of the smart grid. We did this with the following datasets: - Liander Open Data set - Zonnedeal smart meter readings - Mpare smart meter readings