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Urban Energy Ontology

Introduction

The SEMANCO Energy Model is a formal ontology – specified using Web Ontology Language 2 (OWL 2) – comprising concepts captured from diverse sources including standards, use cases and activity descriptions and data sources related to the domains of urban planning and energy management. In particular it contains the terms and attributes that describe regions, cities, neighbourhoods and buildings; energy consumption and CO2 emission indicators, as well as climate and socio- economic factors that influence energy consumption. The ontology enables semantic tools to access the data stemming from different domains and applications. 

 

Standards

The SEMANCO Energy Model is based on existing energy information standards which encompass building data as well as contextual data –climate, economic and social– which impact buildings’ energy efficiency. In particular, energy model terminology is specified in ISO/IEC CD 13273 (Energy efficiency and renewable energy sources), ISO/DTR 16344 (Common terms, definitions and symbols for the overall energy performance rating and certification of buildings), ISO/CD 16346 (Assessment of overall energy performance of buildings), ISO/DIS 12655 (Presentation of real energy use of buildings), ISO/CD 16343 (Methods for expressing energy performance and for energy certification of buildings), and ISO 50001:2011 (Energy management systems – requirements with guidance for use).

 

SEMANCO Ontology describes the domain of urban planning based on the OWL-based translation of the Suggested Upper Merged Ontology(SUMO), available at (http://www.ontologyportal.org/).

Version: 0.3.1
Date of production: 2014-07-30
Language: English
Domains: Urban planning, energy efficiency on buildings

URL to SEMANCO ontology: http://semanco-tools.eu/ontology-releases/eu/semanco/ontology/SEMANCO/SEMANCO.owl
URL to SUMO ontologyhttp://semanco-tools.eu/ontology-releases/eu/semanco/ontology/SUMO/0.1.1...

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References

Deliverable 4.2 Semantic Energy Model 2013 by German Nemirovski and Álvaro Sicilia
An ontology design methodology devised specifically for the project which focuses on the integration of data sources and on facilitating the processing of federated queries. Ontology requirements are captured in the use cases and the activities have been processed to implement the semantic energy model. A semantic energy model described as a formal ontology using Web Ontology Language 2 (OWL 2) is reported. This model comprises concepts gathered from the use cases and the data sources provided by three case studies (Manresa, Copenhagen, Newcastle).

Data Integration Driven Ontology Design, Case Study Smart City. Proceedings of the 13th International Conference on Web Intelligence, Mining and Semantics. WIMS 2013, by German Nemirovski, Andreas Nolle , Álvaro Sicilia, Ilaria Ballarini and Vincenzo Corado
Methods to design of formal ontologies have been in focus of research since the early nineties when their importance and conceivable practical application in engineering sciences had been understood. However, often significant customization of generic methodologies is required when they are applied in tangible scenarios. In this paper, we present a methodology for ontology design developed in the context of data integration. In this scenario, a targeting ontology is applied as a mediator for distinct schemas of individual data sources and, furthermore, as a reference schema for federated data queries. The methodology has been used and evaluated in a case study aiming at integration of buildings’ energy and carbon emission related data. We claim that we have made the design process much more efficient and that there is a high potential to reuse the methodology.

Shared Vocabularies to Support the Creation of Energy Urban Systems Models. ICT for Sustainable places International conference, 2013, by Leandro Madrazo, German Nemirovski and Alvaro Sicilia
The problem of carbon emission reduction in urban areas cannot be constrained to a particular geographical area or scale, nor is it the concern of a particular discipline or expert: it is a systemic problem which involves multiple scales and domains and the collaboration of experts from various fields. The aim of models of urban energy systems is to identify the processes that determine the energy intensity in a specific urban area. Such models can help experts to understand the systems’ behaviour and take measures to improve its performance. The application of semantic technologies can help to create urban energy models which integrate the knowledge from experts in various domains. The goal of the SEMANCO research project is to create a comprehensive framework –i.e. methods and tools– using semantic technologies which enable experts from different domains to devise and deploy urban energy models that help various stakeholders –planners, consultants, policy makers– to understand the complexity underlying carbon reduction in urban areas. A key component of the project is the Semantic Energy Information Framework (SEIF) which facilitates the link between the tools which are intrinsic to an energy model and the required data. This paper describes the process and results obtained in the development of this semantic framework. In particular, the paper discusses the creation of its underlying ontology, that is, the vocabulary shared by different domain experts which is necessary to access the contents of the different data sources required by an energy model. The configuration of the urban energy models and the access to the semantic data and the tools that characterise them take place through the SEMANCO integrated platform. Therefore, the current state of the development of this  platform is also presented in the paper.

 

Copyright (C) 2014 

ARC Enginyeria i Arquitectura La Salle - Universitat Ramon Llull
    Álvaro Sicilia (asicilia@salleurl.edu)

Albstadt-Sigmaringen University
    German Nemirovski (nemirovski@hs-albsig.de),
    Andreas Nolle (nolle@hs-albsig.de),
    Michael Wolters (wolters@hs-albsig.de)


Department of Energy, Politecnico di Torino
    Vincenzo Corado (vincenzo.corrado@polito.it),
    Ilaria Ballarini (ilaria.ballarini@polito.it)