Semantic-based interoperability based on ontologies provide an alternative to centralized stand-ard data models. They help to integrate heterogeneous data produced by loose coupled information systems and to interlink these data with different tools in ad hoc situations. In the SEMANCO project (www.semanco-project.eu) we have used semantic technologies to create energy models of urban areas encompassing a variety of data sources and do-mains (building, geospatial, energy, climate, socioeconomic). The semantically modelled data has been made accessible to a set of simulation and analysis tools. The interoperability among the data sources and between these and the tools that interact with them is assured by a Semantic Energy Information Framework (SEIF) developed in the project. The access to the data and tools takes place in the SEMANCO integrated platform. In this paper we describe the work carried out to integrate an existing simulation software –URSOS– with the semantic data model. The functionalities of the tool and the integrated platform have been demonstrated in an application case carried out in the city of Manresa, in Spain

1. Integrating multiple data sources, domains and tools in
urban energy models using semantic technologies
Leandro Madrazo, ARC Enginyeria i Arquitectura La Salle
Alvaro Sicilia, ARC Enginyeria i Arquitectura La Salle
Joan Pleguezuelos, ARC Enginyeria i Arquitectura La Salle
ECPPM 2014 – 5th eeBDM – Semantic Interoperability for eeB Vienna, 18th September, 2014

2. CONTENTS
1. Interoperability and standards data models
2. Open semantic data models
3. Integration of an energy simulation tool
4. Demonstration case
5. Conclusions

3. SEMANCO is being carried out with the support of the European Union’s FP7 Programme
“ICT for Energy Systems” 2011-2014, under the grant agreement number 287534 .

4. 1. INTEROPERABILITY AND STANDARDS DATA MODELS
“Centralized” approach “Decentralized” approach
Standard
data
model
Domain
1
Domain
3
Domain
2
Domain
4
Standard
data
model
Domain
1
Domain
3
Domain
Domain
4
2
Decentralized and ad-hoc
solutions to interoperability
Centralized standard data models
(e.g. CityGML, IFC)
Including new domains by
extensions mechanisms
Including new domains by
ontology mapping/linking

5. 1. INTEROPERABILITY AND STANDARDS DATA MODELS
The standards data models are aimed at
ensuring interoperability by anticipating, or even
preventing, communication problems between
data and applications.
They provide a priori solution to interoperability
problems between tools, applications and
services by means of a standard data model and
the extension mechanism.
• CityGML  Application Domain Extensions
(ADE)
• IFC  Information Delivery Manual, Model
View Definitions
Standard
data
model
Domain
1
Domain
3
Domain
2
Domain
4
“Centralized” approach

6. 1. INTEROPERABILITY AND STANDARDS DATA MODELS
Standard
data
model
Domain
1
Domain
3
Domain
2
Domain
4
“Centralized” approach
This approach has proved to have some
limitations:
• difficulties to reach a consensus among a
community of users
• lack of flexibility of the data models to adapt
to changes
• the loss of information after exporting and
importing data through applications

7. 1. INTEROPERABILITY AND STANDARDS DATA MODELS
“Decentralized” approach
Standard
data
model
Domain
1
Domain
3
Domain
Domain
4
2
Semantic-based interoperability facilitates the
adoption of decentralized and ad-hoc solutions to
interoperability based on Semantic Web
technologies (RDF, OWL, SPARQL…).
By means of ontologies it is possible to integrate
multiple models, including models created with
standards like CityGML and IFC.
The role of ontologies is to provide bridges
between multiple models. Such ontologies do not
need to be created from scratch but they can be
based on standards like ISO or CEN.

8. 1. INTEROPERABILITY AND STANDARDS DATA MODELS
“Decentralized” approach
Standard
data
model
Domain
1
Domain
3
Domain
Domain
4
2
Semantic-based interoperability brings together
the best of the two worlds:
- a standardization based on the ontologies –
rather than on the data models.
- a decentralization of the data models,
applications and systems which are
interlinked through the ontologies.
Literature relating standard data models and
semantic technologies:
Katranuschkov. P., Gehre, A. & Scherer, R. J. 2003. An ontology
framework to access IFC model data. ITcon 8: 413-437.
Métral, C., Billen, R., Cutting-Decelle, A. F. & Van Ruymbeke, M.
2010. Ontology-based approaches for improving the in-teroperability
between 3D urban models. FormaMente, International
Research Journal on Digital Future 1-2: 85-111
Pont, U., Ghiassi, N., Shayeganfar, F., Mahdavi, A., Fenz, S., Heurix, J.
& Anjomshoaa, A. 2014. SEMRGY: Utilizing semantic web
technologies for performance-guided building design optimization.
ECPPM 2014: 209-214.
Beetz, J., Coebergh, W., Botter, R., Zlatanova, S., & Laat, R. 2014. Interoperable data models for infrastructural artefacts – a novel
IFC extension method using RDF vocabularies exemplified with quay wall structures for harbors. ECPPM 2014: 135-140.
Törmä, S. 2014. Web of building data – integrating IFC with theWeb of Data. ECPPM 2014: 141-147.
Pont, U., Ghiassi, N., Shayeganfar, F., Mahdavi, A., Fenz, S., Heurix, J. & Anjomshoaa, A. 2014. SEMRGY: Utilizing semantic web
technologies for performance-guided building design optimization. ECPPM 2014: 209-214.
Pauwels, P., Corry, E., & O’Donnell, J. 2014. Making SimModel information available as RDF graph. ECPPM 2014: 439-444
Törmä, S. 2014. Web of building data – integrating IFC with theWeb
of Data. ECPPM 2014: 141-147.

9. 2. OPEN SEMANTIC DATA MODELS
In the SEMANCO FP7 project, we have used semantic technologies to
integrate data from multiple domains (socioeconomic, energy, building,
climate, among others) and tools (energy assessment, simulation) in order
to create multiple urban energy models of an urban environment, at
various scales.
Census
Climate
Energy
Building
typologies
Land
registry
Building
systems
Energy analysis
(e.g. data mining)
Energy simulation
(e.g. URSOS)
Energy assessment
(e.g. SAP)

10. 2. OPEN SEMANTIC DATA MODELS
Data connected through the
Semantic Energy Information
Framework
DATA TOOLS

11. 2. OPEN SEMANTIC DATA MODELS
Data connected through the
Semantic Energy Information
Framework
DATA TOOLS

12. 2. OPEN SEMANTIC DATA MODELS
Data connected through the
Semantic Energy Information
Framework
DATA TOOLS

13. 2. OPEN SEMANTIC DATA MODELS
Data connected through the
Semantic Energy Information
Framework
DATA TOOLS

14. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
4
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5

15. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
4
Generation of the 3D model of the
City based on DTM, DSM, and GIS data
provided by the Cities
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5
Semantic integration process (RDB-to-RDF)
based on design patterns, document
templates, tools and editors have been
developed (Nemirovski et al. 2013, Madrazo
et al. 2013).

16. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
1. The user selects a building 4
2. The ID of the selected
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5
building is used to retrieve
the building parameters form
the data sources using
SPARQL:
Cadastre
Census
Building typologies

17. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
1. The user selects a building 4
2. The ID of the selected
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5
building is used to retrieve
the building parameters form
the data sources using
SPARQL:
Cadastre
Census
Building typologies
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: http://www.semanco-project.eu/2012/5/SEMANCO.owl#
SELECT DISTINCT ?year
WHERE {
?b a sumo:Building;
semanco:hasAge [semanco:year_Of_ContructionValue ?year];
semanco:hasBuilding_Cadastral_Data [semanco:hasCadastral_Reference ?ref].
?ref semanco:cadref1Value "2402012".
}

18. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
1. The user selects a building 4
2. The ID of the selected
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5
building is used to retrieve
the building parameters form
the data sources using
SPARQL:
Cadastre
Census
Building typologies
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: <http://www.semanco-project.eu/2012/5/SEMANCO.owl#>
SELECT DISTINCT ?age ?to ?from
WHERE {
?age a semanco:Age_Class .
?age semanco:hasTo_Year ?age_to_instance .
?age_to_instance semanco:toYearValue ?to .
filter(?to >= '1885') .
?age semanco:hasFrom_Year ?age_from_instance2 .
?age_from_instance2 semanco:fromYearValue ?from .
filter(?from <= '1885') .
}
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: http://www.semanco-project.eu/2012/5/SEMANCO.owl#
SELECT DISTINCT ?year
WHERE {
?b a sumo:Building;
semanco:hasAge [semanco:year_Of_ContructionValue ?year];
semanco:hasBuilding_Cadastral_Data [semanco:hasCadastral_Reference ?ref].
?ref semanco:cadref1Value "2402012".
}

19. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: <http://www.semanco-project.eu/2012/5/SEMANCO.owl#>
SELECT DISTINCT ?uvalue
where {
1. The user selects a building 4
2. The ID of the selected
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5
building is used to retrieve
the building parameters form
the data sources using
SPARQL:
Cadastre
Census
Building typologies
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: <http://www.semanco-project.eu/2012/5/SEMANCO.owl#>
SELECT DISTINCT ?age ?to ?from
WHERE {
?age a semanco:Age_Class .
?age semanco:hasTo_Year ?age_to_instance .
?age_to_instance semanco:toYearValue ?to .
filter(?to >= '1885') .
?age semanco:hasFrom_Year ?age_from_instance2 .
?age_from_instance2 semanco:fromYearValue ?from .
filter(?from <= '1885') .
}
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: http://www.semanco-project.eu/2012/5/SEMANCO.owl#
SELECT DISTINCT ?year
WHERE {
?b a sumo:Building;
semanco:hasAge [semanco:year_Of_ContructionValue ?year];
semanco:hasBuilding_Cadastral_Data [semanco:hasCadastral_Reference ?ref].
?ref semanco:cadref1Value "2402012".
}
?b semanco:hasSpace [ semanco:hasCS_Envelope [semanco:hasBottom_Floor ?bf]];
semanco:hasAge <http://www.semanco-project.eu/manresa/age_class/1>.
?bf semanco:hasBottom_Floor_U-value [semanco:bottom_Floor_U-valueValue ?uvalue].
?bf semanco:hasBottom_Floor_Type [semanco:bottom_Floor_TypeValue "Bottom"].
}

20. 3. INTEGRATION OF AN ENERGY SIMULATION TOOL
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: <http://www.semanco-project.eu/2012/5/SEMANCO.owl#>
SELECT DISTINCT ?uvalue
where {
1. The user selects a building 4
2. The ID of the selected
3D Maps URSOS Input form
Integrated Platform
URSOS Energy
calculation engine
GIS data
Census Climate Cadastre
Typology Socio-Economic
Ontology
OWL-DL liteA
ELITE
Federation engine
Energy-related data Semantic Energy
Information Framework
1
2
3 5
building is used to retrieve
the building parameters form
the data sources using
SPARQL:
Cadastre
Census
Building typologies
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: <http://www.semanco-project.eu/2012/5/SEMANCO.owl#>
SELECT DISTINCT ?age ?to ?from
WHERE {
?age a semanco:Age_Class .
?age semanco:hasTo_Year ?age_to_instance .
?age_to_instance semanco:toYearValue ?to .
filter(?to >= '1885') .
?age semanco:hasFrom_Year ?age_from_instance2 .
?age_from_instance2 semanco:fromYearValue ?from .
filter(?from <= '1885') .
}
prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: http://www.semanco-project.eu/2012/5/SEMANCO.owl#
SELECT DISTINCT ?year
WHERE {
?b a sumo:Building;
semanco:hasAge [semanco:year_Of_ContructionValue ?year];
semanco:hasBuilding_Cadastral_Data [semanco:hasCadastral_Reference ?ref].
?ref semanco:cadref1Value "2402012".
}
?b semanco:hasSpace [ semanco:hasCS_Envelope [semanco:hasBottom_Floor ?bf]];
semanco:hasAge <http://www.semanco-project.eu/manresa/age_class/1>.
?bf semanco:hasBottom_Floor_U-value [semanco:bottom_Floor_U-valueValue ?uvalue].
?bf semanco:hasBottom_Floor_Type [semanco:bottom_Floor_TypeValue "Bottom"].
}

21. SEMANCO Platform web interface displaying
the 3D model of the Manresa city

22. Pop-up window with the details
of the selected building

23. Input form for URSOS parameters:
Building properties

24. Input form for URSOS parameters:
Occupancy parameters

25. Input form for URSOS parameters:
System parameters

26. Input form for URSOS parameters:
Energy outputs

27. CONCLUSIONS
The integration of URSOS in the SEMANCO platform has
empirically proved that semantic technologies can help to
solve interoperability by facilitating the communication
between semantically modelled data obtained from multiple
sources and existing energy simulation tools.
It has been demonstrated that the users could carry out
energy performance analysis using an external tool which is
fed with multi-domain and distributed data which has been
semantically modelled.

28. CONCLUSIONS
More information:
www.semanco-project-eu
SEMANCO is being carried out with the support of the European Union’s FP7 Programme
“ICT for Energy Systems” 2011-2014, under the grant agreement number 287534 .