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Investigating result quality indicators in industry foundation classes to city geography markup language conversion

Soini, Ville-Pekka LU (2019) In Student thesis series INES NGEM01 20191
Dept of Physical Geography and Ecosystem Science
Abstract
Industry Foundation Classes (IFC) models from the Architecture, Engineering and
Construction (AEC) -industries can contain information on building life-cycle entities.
Urban planning and related domains are interested in data conversions between IFC
and City Geography Markup Language (CityGML) because of this. However, the
maintenance and versioning of CityGML life-cycle building data poses a serious
challenge. Semantics play a big role in CityGML data contents in addition to
converted objects. General methods for testing data conversion result for quality are
not strongly present in the prevailing research literature. The evaluation of CityGML
file contents and conversion quality are therefore challenging.
CityGML is a... (More)
Industry Foundation Classes (IFC) models from the Architecture, Engineering and
Construction (AEC) -industries can contain information on building life-cycle entities.
Urban planning and related domains are interested in data conversions between IFC
and City Geography Markup Language (CityGML) because of this. However, the
maintenance and versioning of CityGML life-cycle building data poses a serious
challenge. Semantics play a big role in CityGML data contents in addition to
converted objects. General methods for testing data conversion result for quality are
not strongly present in the prevailing research literature. The evaluation of CityGML
file contents and conversion quality are therefore challenging.
CityGML is a Three-dimensional (3D) data format created for storing 3D city data
into databases. The exchange of life-cycle data from BIM environments enables more
spatial analyses on urban and environmental related data.
This master thesis explores methods that are in use for evaluating conversions and
data accuracies within the realms of Building Information Modelling (BIM) and
geodata by researching application requirements and measures for quality in a case
study.
The INSPIRE directive implementation guides distribution of public domain geodata
in the EU and gives instructions on implementing CityGML. Different applications of
CityGML and their requirements are leading to the creation of national guidelines. A
literature study/review conducted revealed four different main sources for CityGML
data requirements.
An explorative case study compares four different IFC models from the GeoBIM
benchmark testbench data. The conversion tools FME 2017 and ArcGIS PRO Data
Interoperability extension are used to convert the GeoBIM benchmark IFC data to
CityGML 2.0 Level-of-Detail (LOD) 3 and LOD4 data. A total of ten test methods are
performed to assess the quality of IFC to CityGML conversion data.
The evaluation results for the quality indicators created in the case study reveal that
most metrics used for indicating quality of IFC to CityGML 2.0 data conversions are
applicable for single LOD4 features but are more difficult to interpret for LOD3.
The results from the study reveal that the conversion methodologies for IFC data
should be verified before tackling performance and optimisation issues. Metrics for
deriving positional accuracies within the data conversion geometries and those taking
advantage of the FME data inspector features are easier to apply. Detailed findings
from the case study data conversions revealed more interesting facts about the data
evaluation methods and conversion workflows.
There is a severe lack of automated eXtensible Markup Language (XML) formatters
for writing CityGML. More study is also required on the documentation of data
conversion methods. (Less)
Popular Abstract
Industry Foundation Classes (IFC) models from the Architecture, Engineering and Construction (AEC) -industries can contain information on building life-cycle entities. Urban planning and related domains are interested in data conversions between IFC and City Geography Markup Language (CityGML) because of this. However, the maintenance and versioning of CityGML life-cycle building data poses a serious challenge. Semantics play a big role in CityGML data contents in addition to converted objects. General methods for testing data conversion result for quality are not strongly present in the prevailing research literature. The evaluation of CityGML file contents and conversion quality are therefore challenging.

CityGML is a... (More)
Industry Foundation Classes (IFC) models from the Architecture, Engineering and Construction (AEC) -industries can contain information on building life-cycle entities. Urban planning and related domains are interested in data conversions between IFC and City Geography Markup Language (CityGML) because of this. However, the maintenance and versioning of CityGML life-cycle building data poses a serious challenge. Semantics play a big role in CityGML data contents in addition to converted objects. General methods for testing data conversion result for quality are not strongly present in the prevailing research literature. The evaluation of CityGML file contents and conversion quality are therefore challenging.

CityGML is a Three-dimensional (3D) data format created for storing 3D city data into databases. The exchange of life-cycle data from BIM environments enables more spatial analyses on urban and environmental related data.

This master thesis explores methods that are in use for evaluating conversions and data accuracies within the realms of Building Information Modelling (BIM) and geodata by researching application requirements and measures for quality in a case study.

The INSPIRE directive implementation guides distribution of public domain geodata in the EU and gives instructions on implementing CityGML. Different applications of CityGML and their requirements are leading to the creation of national guidelines. A literature study/review conducted revealed four different main sources for CityGML data requirements.

An explorative case study compares four different IFC models from the GeoBIM benchmark testbench data. The conversion tools FME 2017 and ArcGIS PRO Data Interoperability extension are used to convert the GeoBIM benchmark IFC data to CityGML 2.0 Level-of-Detail (LOD) 3 and LOD4 data. A total of ten test methods are performed to assess the quality of IFC to CityGML conversion data.

The evaluation results for the quality indicators created in the case study reveal that most metrics used for indicating quality of IFC to CityGML 2.0 data conversions are applicable for single LOD4 features but are more difficult to interpret for LOD3.

The results from the study reveal that the conversion methodologies for IFC data should be verified before tackling performance and optimisation issues. Metrics for deriving positional accuracies within the data conversion geometries and those taking advantage of the FME data inspector features are easier to apply. Detailed findings from the case study data conversions revealed more interesting facts about the data evaluation methods and conversion workflows.

There is a severe lack of automated eXtensible Markup Language (XML) formatters for writing CityGML. More study is also required on the documentation of data conversion methods. (Less)
Please use this url to cite or link to this publication:
author
Soini, Ville-Pekka LU
supervisor
organization
course
NGEM01 20191
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Physical Geography, CityGML 2.0, IFC, BIM, Geodata, Conversion, FME, Quality, Evaluation, GeoBIM, Geomatics
publication/series
Student thesis series INES
report number
495
language
English
id
8996029
date added to LUP
2019-10-02 12:27:39
date last changed
2019-10-02 12:27:39
@misc{8996029,
  abstract     = {{Industry Foundation Classes (IFC) models from the Architecture, Engineering and 
Construction (AEC) -industries can contain information on building life-cycle entities.
Urban planning and related domains are interested in data conversions between IFC 
and City Geography Markup Language (CityGML) because of this. However, the 
maintenance and versioning of CityGML life-cycle building data poses a serious 
challenge. Semantics play a big role in CityGML data contents in addition to 
converted objects. General methods for testing data conversion result for quality are 
not strongly present in the prevailing research literature. The evaluation of CityGML 
file contents and conversion quality are therefore challenging. 
CityGML is a Three-dimensional (3D) data format created for storing 3D city data 
into databases. The exchange of life-cycle data from BIM environments enables more 
spatial analyses on urban and environmental related data.
This master thesis explores methods that are in use for evaluating conversions and 
data accuracies within the realms of Building Information Modelling (BIM) and 
geodata by researching application requirements and measures for quality in a case 
study.
The INSPIRE directive implementation guides distribution of public domain geodata 
in the EU and gives instructions on implementing CityGML. Different applications of
CityGML and their requirements are leading to the creation of national guidelines. A 
literature study/review conducted revealed four different main sources for CityGML 
data requirements.
An explorative case study compares four different IFC models from the GeoBIM 
benchmark testbench data. The conversion tools FME 2017 and ArcGIS PRO Data 
Interoperability extension are used to convert the GeoBIM benchmark IFC data to 
CityGML 2.0 Level-of-Detail (LOD) 3 and LOD4 data. A total of ten test methods are
performed to assess the quality of IFC to CityGML conversion data.
The evaluation results for the quality indicators created in the case study reveal that 
most metrics used for indicating quality of IFC to CityGML 2.0 data conversions are 
applicable for single LOD4 features but are more difficult to interpret for LOD3.
The results from the study reveal that the conversion methodologies for IFC data 
should be verified before tackling performance and optimisation issues. Metrics for 
deriving positional accuracies within the data conversion geometries and those taking 
advantage of the FME data inspector features are easier to apply. Detailed findings 
from the case study data conversions revealed more interesting facts about the data 
evaluation methods and conversion workflows.
There is a severe lack of automated eXtensible Markup Language (XML) formatters 
for writing CityGML. More study is also required on the documentation of data 
conversion methods.}},
  author       = {{Soini, Ville-Pekka}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Student thesis series INES}},
  title        = {{Investigating result quality indicators in industry foundation classes to city geography markup language conversion}},
  year         = {{2019}},
}