=Paper=
{{Paper
|id=Vol-3081/10paper
|storemode=property
|title=Interoperability between BIM and GIS through open data standards: An overview of current literature
|pdfUrl=https://ceur-ws.org/Vol-3081/10paper.pdf
|volume=Vol-3081
|authors=Eyosias Guyo,Timo Hartmann,Lucian Ungureanu
|dblpUrl=https://dblp.org/rec/conf/ldac/GuyoHU21
}}
==Interoperability between BIM and GIS through open data standards: An overview of current literature==
https://ceur-ws.org/Vol-3081/10paper.pdf
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
Interoperability between BIM and GIS through open
data standards: An overview of current literature
Eyosias Guyo1, 2, Timo Hartmann1, Lucian Ungureanu1
1 Technische Universität Berlin, Berlin, Germany
2 Trimble Solutions Oy, Espoo, Finland
eyosias.guyo@trimble.com
Abstract. Building information modeling (BIM) allows representation of de-
tailed information regarding building elements while geographic information
system (GIS) allows representation of spatial information about buildings and
their surroundings. Overlapping these domains will combine their individual fea-
tures and provide support to important activities such as building emergency re-
sponse, construction site safety, construction supply chain management, and sus-
tainable urban design. Interoperability through open data standards is one method
of connecting software tools from BIM and GIS domains. However, no single
open data standard available today can support all information from the two do-
mains. As a result, many researchers have been working to overlap or connect
different open data standards to enhance interoperability. An overview of these
studies will help identify the different approaches used and determine the ap-
proach with the most potential to enhance interoperability. This paper adopted a
strong definition of interoperability using information technology (IT) based
standard documents. Based on this definition, previous approaches towards im-
proving interoperability between BIM and GIS applications through open data
standards were studied. The result shows previous approaches have implemented
data conversion, data integration, and linked data approaches. Between these
methods, linked data emerged as having the most potential to connect open data
standards and expand interoperability between BIM and GIS applications be-
cause it allows information exchange without editing the original data. The paper
also identifies the main challenges in implementing linked data technologies for
interoperability and provides directions for future research.
Keywords: BIM, GIS, Interoperability, Open data standards
1 Introduction
Building information modeling (BIM) and geographic information system (GIS) are
technology-driven domains with important interrelation. BIM allows representation of
data regarding all building elements [1] and it can support the planning, construction
and operation of buildings. Meanwhile, GIS allows representation of spatial data re-
garding a certain environment including buildings [2]. This puts buildings at an inter-
section between BIM and GIS domains. A cooperation between these two domains is
Copyright 2021 for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0)
115
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
important to manage the built environment since the construction and operation of
buildings affect their environment [3], and inversely, environmental aspects influence
the planning, construction, and operation of buildings [4]. Benefits of such cooperation
can include improved construction site safety, enhanced construction supply chain
management, improved building emergency management, and sustainable urban de-
sign [3, 5-9].
BIM and GIS tools, however, have some significant differences that make collabo-
ration a challenge. Originally, BIM tools were aimed at supporting the design of new
objects with various levels of detail, while GIS tools were used to represent spatial data
regarding objects that already exist in an environment [10]. Hence, they evolved differ-
ently [4]. They differ in data structure, in geometry representation, in level of develop-
ment, and in the coordinate system they use [11]. As a result, even though the effort to
integrate the two domains has been increasing in the past years [3], joining the domains
remains a challenge. The objective of this paper is to investigate previous integration
approaches and determine which of the approaches have the most potential to improve
cooperation between BIM and GIS tools. The paper will also identify challenges and
future research directions.
Amirebrahimi et al. [6] classified BIM and GIS integration levels into application
level, process level, and data level integration. This paper will focus on data level inte-
gration through open data standards. The paper is structured as follows. In Section 2,
we adopt information technology (IT) based definition of interoperability from interna-
tional documents. In Section 3 we present some open data standards from BIM and GIS
that can play a key role in interoperability between the two domains. No single open
data standard, however, can fully support information exchange between BIM and GIS.
Therefore, the data standards should be overlapped or connected with one another. And
that will be the focus of Section 4 where previous approaches to connect open data
standards are discussed. The accomplishments and shortcomings of these approaches
will be presented in the same section. In Section 5 and 6 discussions and conclusions
are presented along with challenges and future research directions.
2 Working definition of Interoperability
Interoperability is defined in different ways in different domains [12]. Therefore, we
decided to adopt a well-established definition for interoperability before discussing the
topic. Interoperability between software tools is an IT based concept. Hence, to estab-
lish a strong definition for the term, we decided to explore IT based definitions. For this
purpose, we considered IEEE Standard Glossary of Software Engineering Terminology
published by Institute of Electrical and Electronics Engineers (IEEE) [13] and Infor-
mation Technology – Vocabulary jointly published by the International Organization
for Standardization (ISO) and the International Electrotechnical Commission
(IEC) [14]. ISO/IEC defines multiple types or features of interoperability such as syn-
tactic interoperability, semantic data interoperability, and behavioral interoperabil-
ity [15]. For this paper, we will use the general definition of the term given on
ISO/IEC 2382:2015 to simplify the discussion. We also identified the definition of
116
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
‘integration’ and ‘conversion’ as these concepts are sometimes mistakenly used in in-
teroperability discussions within the literature as being synonymous.
Table 1. Definitions of important terms based on international standards
Terms IEEE [13] ISO/IEC [14]
“The ability of two or more The capability to communicate,
systems or components to ex- or exchange data between different
Interoperability change information and to use functional units in a manner that
the information that has been demands the user to have little or
exchanged”. no knowledge regarding each unit
“The process of combining “progressive assembling of sys-
Integration software components, hard- tem components into the whole
ware components, or both system”
into an overall system”.
“Modification of existing Changing “the representation of
software to enable it to oper- data from one form to another,
Conversion ate with similar functional ca- without changing the information
pability in a different environ- conveyed”.
ment”.
The IT based definitions presented in Table 1 articulate what interoperability is and
what it is not. Interoperability is not conversion or modification of data representation.
It is also not combining or assembling data models into one. Rather, we define it as the
ability to communicate and exchange information between different software tools and
use the information exchanged. The software tools, in this paper’s context, are applica-
tions from BIM and GIS domains. This definition will be used as a requirement to eval-
uate interoperability approaches in this paper.
3 Interoperability through open data standards
There are different approaches to achieve interoperability between BIM and GIS tools.
These approaches involve either reconfiguring the tools or modifying work processes
or using open data standards [6]. This paper focuses on interoperability through open
data standards. These open standards allow exchange of information between different
software tools without requiring users to have a vendor specific software package [16].
The following subsections present some of the open data standards available for BIM
and GIS and their capacity to go beyond their original scope and contribute towards
BIM and GIS interoperability. The open data standards were selected by running a term
co-occurrence analysis using VOSviewer on the 41 literatures referenced in this paper.
The analysis identified CityGML (47 occurrences), IFC (31 occurrences), IndoorGML
(22 occurrences) and LandInfra (8 occurrences) as open data standards with multiple
occurrences.
117
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
3.1 CityGML
City Geography Markup Language (CityGML) is an XML-based data model widely
implemented for the representation and exchange of 3D city models [17]. It is an Open
Geospatial Consortium (OGC) standard that can represent built structures (buildings,
tunnels, bridges, and roads) and environmental aspects (elevation, vegetation, water
bodies and more) [18].
CityGML provides two concepts to support the exchange of features that are not
explicitly represented in the schema [18]. One is the concept of generic objects and
attributes. This concept allows features that are not explicitly represented in CityGML
to be modelled using generic objects. The second concept is application domain exten-
sion (ADE) which allows addition of new features and information to existing
CityGML classes without altering the semantic structure of CityGML [18, 19]. ADEs
have played an important role in some of BIM-GIS collaboration efforts such as de Laat
and van Berlo [20] and Deng et al. [21]. However, its use may not be supported by some
software packages [20, 21].
Another important CityGML feature in BIM-GIS integration discussions is the con-
cept of level of details (LODs). CityGML supports 5 LODs. At the lowest level there
is LOD0 where buildings are represented by footprint or roof edge polygons. And at
the highest level we have LOD4 where buildings are modeled with detailed elements
including indoor space representations [18]. This concept supports integration efforts
since features represented in similar LODs can be integrated more smoothly than fea-
tures of different LoDs [22].
3.2 Industry Foundation Classes (IFC)
The Industry Foundation Classes (IFC) is an open source file format developed to ena-
ble interoperability between BIM software tools [16]. It is developed by build-
ingSMART International and it is the basis for ISO 16739-1:2018 [23]. Its data schema
is defined in EXPRESS data specification language (defined in ISO 10303-11) and in
XML Schema definition language (XSD) [24]. Currently, buildingSMART is working
on IFC extensions to represent infrastructure facilities (such as railways, roads and
bridges) which can enhance IFC’s role in cross-domain collaboration between BIM and
GIS tools [17].
3.3 IndoorGML
IndoorGML is another OGC open data standard and it is an XML-based schema for
indoor spatial information [25]. Unlike IFC, which focuses on building component fea-
tures, IndoorGML mainly focuses on representation of indoor space structures as well
as interoperability between indoor spatial information tools [26]. It also provides ex-
tensive support for indoor navigation [27].
IndoorGML includes only a minimum set of geometric and semantic components to
avoid overlapping with standards such as IFC and CityGML [25]. Therefore, it is ben-
eficial to align it with these other standards [28]. IndoorGML permits such alignment
118
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
by allowing referencing of objects in external datasets such as IFC and CityGML [25].
Through this referencing feature, IndoorGML has the potential to contribute to cross-
domain collaboration between BIM and GIS tools.
3.4 LandInfra
LandInfra is a relatively new OGC standard [29]. It is a conceptual model for land and
civil engineering infrastructure and it is published for predetermined use cases (facili-
ties, projects, alignment, road, railway, survey, land features and land division) [30].
LandInfra has some potential overlap with CityGML. However, unlike CityGML, it
does not have the concept of extension and LODs [29]. It does, however, support some
features that are not available in CityGML nor IFC. These include: supporting subsur-
face data modeling, providing a framework to model legal information of buildings and
storing survey related information [31].
© Ordnance Survey Limited 2021
Fig. 1. Real-world objects represented by IFC, CityGML and LandInfra (Dark shading indicates
strong coverage, light shading weaker coverage (or under development) and no shading implies
no known coverage.) [32]
In summary, the open data standards presented in this section are developed with a
specific scope in mind. IFC (currently) is for building information modeling, CityGML
is for 3D virtual city modeling, IndoorGML is for indoor space modeling and naviga-
tion, and LandInfra is for land and civil engineering infrastructure. Figure 1 presents
three of these data standards (IFC, CityGML and LandInfra) and various objects from
BIM and GIS they support. As it can be seen in the figure, each standard supports only
a portion of all the objects available. Although some of the standards have features that
allow them to be extended beyond their original scope, no single standard can support
all data exchange requirements between BIM and GIS. While interoperability does not
necessitate complete data exchange, the lack of complete representation by the open
data standard implies there exists data that cannot be exchanged using these data stand-
ards. As a result, researchers have been attempting to overlap or connect these open
data standards with one another to improve data exchange between BIM and GIS.
119
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
4 Connecting BIM and GIS data standards
Previous studies that proposed different methods to connect open data standards from
BIM and GIS are summarized in this section. Their contribution towards improving
interoperability between BIM and GIS domains is discussed based on the definition of
interoperability articulated in Section 2. The methods identified are categorized into
data standard conversion, data standard integration, and linked data approach based
on the process they implemented. It should be noted that some methods involved more
than one of these processes.
4.1 Data standard conversion
Most of the previous BIM-GIS data standard integration methods focused on conver-
sion of IFC to CityGML [3]. de Laat and van Berlo [20] proposed a unidirectional con-
version where geometry of building objects and their properties (semantic information)
stored in IFC format can be transformed to CityGML LOD4. Deng et al. [21] proposed
a bidirectional exchange of geometrical information between IFC and CityGML as well
as a unidirectional transformation of semantic information from IFC to CityGML. Both
studies created new CityGML extensions (ADEs) to implement the conversion. These
methods will work only if GIS applications are able to work with the new extensions
which may not always be the case as revealed in the studies. A study by Donkers et
al. [33] presented a unidirectional conversion algorithm to convert geometrical and se-
mantic information from IFC model to CityGML LOD3 building model which does not
include building interiors like CityGML LOD4. There was also a proposal to extract
indoor building information from IFC into IndoorGML [34].
Some commercial software tools provide data conversion services, mostly from IFC
to CityGML. Feature Manipulation Engine (FME) provides such service and it has been
used by studies such as Yu and Teo [35] and Jusuf et al. [9]. Similarly ArcGIS and its
data interoperability extension were used for conversion of BIM data into GIS data by
studies such as Amirebrahimi et al. [6] and Tashakkori et al. [7].
Overall, the studies in this group proposed to exchange information between BIM
and GIS by converting one data standard into another. The conversions are mostly uni-
directional conversion from BIM to GIS (IFC to CityGML) which neglects the other
half of the information exchange requirement that is from GIS to BIM. Moreover, even
though some information can be transferred through conversion, the process alters and
modifies the original data model. This results in data loss and inconsistencies [11, 17].
And the outputs are not always supported by the target software tools. Because of these
drawbacks, the studies in this category fall short of meeting the requirements of interop-
erability established in Section 2.
4.2 Data standard integration
In this category, there are studies that propose aggregating both BIM and GIS data into
a single unified model or database. A notable example is El-Mekawy et al. [8] who
presented a unified building model (UBM) where all classes and concepts from IFC
120
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
and CityGML would be aggregated. ArcGIS, a GIS software, was chosen to implement
this model. When compared with methods that convert IFC into CityGML, the UBM
method results in less information loss. However, the information exchange remains
one directional, that is from BIM tools to GIS tools.
Wyszomirski and Gotlib [2] proposed to combine data from IFC and CityGML mod-
els and store it in a single database. The aim is to allow BIM and GIS tools to share
information by sending and retrieving data to and from a database. However, BIM ap-
plications that are currently available on the market do not have mechanisms to work
with data stored in a database.
The methods grouped in this section were able to reduce data loss by integrating IFC
and CityGML data standards together instead of converting one into the other. How-
ever, whether fully integrating different models is favorable or not is questioned by
some authors as it can create data ownership and intellectual property rights issues [11,
36]. Furthermore, the proposed methods favor GIS tools since those tools are the ones
that get access to the integrated data. Therefore, methods in this group do not suffi-
ciently satisfy the requirements of interoperability defined in Section 2.
4.3 Linked data for interoperability
Studies grouped in this category used linked data approaches to link BIM and GIS data
standards. Hor et al. [37] proposed to link BIM and GIS through semantic web technol-
ogies by developing a semantic graph database framework using IFC and CityGML
source datasets. They provided a web-based application to simulate the integrated
model. However, practical use cases of the integration were not discussed in detail.
Vilgertshofer et al. [17] used a linked data approach to connect a BIM-based tunnel
model with its corresponding GIS model by converting IFC and CityGML into web
ontology language (OWL) representation and establishing a link between them. OWL
is a language in semantic web technologies that is used to represent rich and complex
knowledge [38]. Using OWL representation to establish the link allowed the authors to
use semantic web querying language SPARQL to query data from IFC and CityGML.
Similarly, Karan et al. [10] proposed to create semantic web representation of BIM
and GIS data , so that it can be processed by semantic web applications. They developed
an ontological representation of IFC and linked that to selected existing GIS ontologies.
The result was an extended ontology with concepts from BIM and GIS that were rele-
vant to a specific use case (monitoring construction supply chain management). Then,
using SPARQL, information could be retrieved from the combined dataset. The authors
were able to represent the query results in ifcXML building model which can be loaded
into BIM tools. They also used CSV format to represent the query result in GIS tools.
The studies categorized in this group developed a semantic web representation of
BIM and GIS data standards and created a link between the web representation (rather
than converting one data standard into another). Hence the original data remained un-
changed. Only selected data was transferred instead of all the data. And the results could
be created in formats that can be used by both BIM and GIS tools. These characteristics
make the linked data approaches exceedingly favorable for interoperability use between
BIM and GIS tools.
121
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
Semantic web approaches are gaining popularity in BIM-GIS collaboration re-
searches [3]. Availability of BIM and GIS web standards can contribute to such studies.
IFC schema is available in OWL ontology (ifcOWL) which provides the opportunity
to represent building data in Resource Description Framework (RDF) graphs [1]. RDF
is a framework used to publish and interlink data on the web [39]. Geospatial data can
also be represented in the semantic web using standards such as GeoSPARQL and
stRDF. GeoSPARQL provides a vocabulary for representation of geospatial data in
RDF and it also defines a SPARQL extension to process geospatial data [40]. stRDF
extends RDF with the ability to represent spatial and temporal data and it can be queried
using stSPARQL which is an extension of SPARQL [41].
However, semantic web approaches have some critical issues. Ontologies developed
by multidisciplinary professionals (BIM and GIS in the current context) may lead to
inconsistency [10]. Establishing agreement between the different ontologies is a chal-
lenge [24]. Additionally, the technologies require some understanding of graph mathe-
matics, graph databases structure and related tools in addition to understanding BIM
and GIS knowledge data structure and schema characteristics [37]. And finally, the
methods were implemented on limited use cases. Therefore, further studies that imple-
ment semantic web approaches to other use cases is necessary to better understand and
evaluate these methods.
5 Discussion
This paper embraces an IT-based definition of interoperability extracted from IEEE and
ISO/IEC standards. We defined interoperability as the ability to communicate and ex-
change information between different software tools and be able to use the exchanged
information. Among the different methods that can be implemented to provide interop-
erability between BIM and GIS tools, the use of open data standards was the focus of
this paper.
We presented some of the open data standards available in BIM and GIS (IFC,
CityGML, IndoorGML and LandInfra) in Section 3. The interoperability role these
standards play in their respective domain (For example CityGML in 3D virtual city
modeling) and their capacity to extend beyond their original scope and support cross-
domain collaboration between BIM and GIS tools (for example ADEs in CityGML)
were discussed. However, currently, none of these standards can support all data ex-
change requirements between BIM and GIS. Even though interoperability does not ne-
cessitate complete data exchange, the lack of complete representation by the open data
standard indicates that there exists data that cannot be exchanged while using these data
standards. Therefore, to enhance interoperability, the data standards could be over-
lapped or connected with one another.
Several studies have proposed several approaches to connect BIM and GIS data
standards. These proposals were grouped into three in this paper. The first group pro-
posed to convert one data standard into another. Some information could be transferred
between BIM and GIS tools through these conversion methods. However, the conver-
sion process alters and modifies data representation resulting in data inconsistency and
122
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
data loss. Moreover, most of the conversion methods are unidirectional transformations
(from BIM to GIS) that cover only one side of the information exchange requirement.
And at times, the outputs were not supported by the target applications. Hence, these
approaches fail to correspond with the definition of interoperability established in Sec-
tion 2 of this paper.
The second group of approaches proposed to combine data standards from BIM and
GIS domains (in IFC and CityGML format) and store it in a unified model or database.
These methods allow information from BIM and GIS domains to be aggregated and
stored together. However, it was the GIS tools that had access to the aggregated data.
That means data is transferred from BIM to GIS but not vice versa. Therefore, these
methods fell to meet the requirements of interoperability established in this paper.
The third group of BIM-GIS interoperability studies identified were studies that cre-
ated links between different data standards through linked data and semantic web tech-
nologies. This approach allows different models to remain separate and stored in their
original form while selected information is shared between them without loss of mean-
ing [11]. The outputs could be given in formats that are supported by both BIM and GIS
tools. These important characteristics of linked data approaches complies with the def-
inition of interoperability adopted in Section 2 of this paper.
Although semantic web technologies are identified as promising methods to link data
models, they still have certain issues. Establishing agreement between different ontol-
ogies from different disciplines is a crucial challenge [24]. One way to address this
issue could be through formalization of AEC ontologies [10]. Currently, there are dis-
cussions as to whether to create a central ontology and build everything else around it
or manage data in a completely decentralized manner [24]. Another challenge is that
these technologies require some understanding of graph mathematics, graph database
structure and related concepts [37].
6 Conclusion
The relationship between buildings and their surrounding environment calls for a col-
laboration between BIM and GIS domains. BIM supports the design, construction, and
operation of the buildings while GIS supports spatial data regarding the surrounding of
those buildings as well as their inside space. Interoperability between software tools
from the two domains will allow us to combine their functionality and leverage it for
better management of the built environment.
To discuss interoperability between BIM and GIS tools, it is necessary to have a
well-developed definition of interoperability. Hence, this paper began by adopting a
definition of interoperability from IEEE and ISO/ IEC standards. Then, between the
different approaches towards interoperability, this paper focused on the use of open
data standards. Some open data standards from BIM and GIS were presented and their
potential to support cross-domain interoperability between BIM and GIS was dis-
cussed. However, since none of the open data standards support all necessary data ex-
change requirements, they need to be overlapped or connected with one another to im-
prove interoperability.
123
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
There were many approaches in the past to connect open data standards from BIM
and GIS. These approaches were summarized in this paper and were classified into data
standard conversion, data standard integration and linked data approach. Among these,
the use of linked data methods to create a link between BIM and GIS data standards
was identified as a promising approach to enhance interoperability for the fundamental
reason that it allows information exchange without editing the original data. However,
harmonization between knowledge bases created by different domains remains a chal-
lenge to the linked data methods. Furthermore, additional use case-based studies that
implement linked data methods to exchange information between BIM and GIS tools
are necessary to further understand the role linked data methods can play in the interop-
erability discussion.
Acknowledgment
This project is receiving funding from the European Union’s Horizon 2020 research
and innovation programme under the Marie Skłodowska-Curie grant agreement No
860555.
References
1. Pauwels, P. and Terkaj, W., EXPRESS to OWL for construction industry: Towards a
recommendable and usable ifcOWL ontology, Autom. Constr., vol. 63, pp. 100–133, (2016),
doi: 10.1016/j.autcon.2015.12.003.
2. Wyszomirski, M. and Gotlib, D., A Unified Database Solution to Process BIM and GIS
Data, Appl. Sci., vol. 10, no. 23, (2020), doi: 10.3390/app10238518.
3. Wang, H., Pan, Y., and Luo, X., Integration of BIM and GIS in sustainable built
environment: A review and bibliometric analysis, Automation in Construction, vol. 103.
Elsevier B.V., pp. 41–52, (Jul. 01, 2019), doi: 10.1016/j.autcon.2019.03.005.
4. Zhu, J., Wright, G., Wang, J., and Wang, X., A Critical Review of the Integration of
Geographic Information System and Building Information Modelling at the Data Level,
ISPRS Int. J. Geo-Information, vol. 7, no. 2: 66, (2018), doi: 10.3390/ijgi7020066.
5. Irizarry, J., Karan, E. P., and Jalaei, F., Integrating BIM and GIS to improve the visual
monitoring of construction supply chain management, Autom. Constr., vol. 31, pp. 241–
254, (2013), doi: 10.1016/j.autcon.2012.12.005.
6. Amirebrahimi, S., Rajabifard, A., Mendis, P., and Ngo, T., A data model for integrating GIS
and BIM for assessment and 3D visualisation of flood damage to building, in CEUR
Workshop Proceedings, (2015), vol. 1323, pp. 78–89.
7. Tashakkori, H., Rajabifard, A., and Kalantari, M., A new 3D indoor/outdoor spatial model
for indoor emergency response facilitation, Build. Environ., vol. 89, pp. 170–182, (2015),
doi: 10.1016/j.buildenv.2015.02.036.
8. El-Mekawy, M., Östman, A., and Hijazi, I., A unified building model for 3D urban GIS,
ISPRS Int. J. Geo-Information, vol. 1, no. 2, pp. 120–145, (2012), doi: 10.3390/ijgi1020120.
9. Jusuf, S., Mousseau, B., Godfroid, G., and Soh, J., Path to an Integrated Modelling between
IFC and CityGML for Neighborhood Scale Modelling, Urban Sci., vol. 1, no. 3: 25, (2017),
doi: 10.3390/urbansci1030025.
124
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
10. Karan, E. P., Irizarry, J., and Haymaker, J., BIM and GIS Integration and Interoperability
Based on Semantic Web Technology, J. Comput. Civ. Eng., vol. 30, no. 3, (2016), doi:
10.1061/(asce)cp.1943-5487.0000519.
11. Herle, S., Becker, R., Wollenberg, R., and Blankenbach, J., GIM and BIM: How to Obtain
Interoperability Between Geospatial and Building Information Modelling?, PFG - J.
Photogramm. Remote Sens. Geoinf. Sci., vol. 88, no. 1, pp. 33–42, (2020), doi:
10.1007/s41064-020-00090-4.
12. International Organization for Standardization, Advanced automation technologies and their
applications — Requirements for establishing manufacturing enterprise process
interoperability — Part 1: Framework for enterprise interoperability (ISO 11354-1:2011).
(2011).
13. The Institute of Electrical and Electronics Engineers (IEEE), IEEE Standard Glossary of
Software Engineering Terminology. (1990).
14. International Organization for Standardization (ISO), ISO/IEC 2382:2015 Information
technology — Vocabulary, 1st ed. (2015).
15. International Organization for Standardization (ISO), ISO/IEC 19941:2017 Information
technology — Cloud computing — Interoperability and portability. (2017).
16. Laakso, M. and Kiviniemi, A., The IFC standard - A review of history, development, and
standardization, J. Inf. Technol. Constr., vol. 17, pp. 134–161, (2012).
17. Vilgertshofer, S., Amann, J., Willenborg, B., Borrmann, A., and Kolbe, T. H., Linking BIM
and GIS models in infrastructure by example of IFC and CityGML, in ASCE International
Workshop on Computing in Civil Engineering 2017, (2017), pp. 133–140, doi:
10.1061/9780784480823.017.
18. Open Geospatial Consortium, OpenGIS City Geography Markup Language (CityGML)
Encoding Standard, Version 2.0.0. (2012).
19. Biljecki, F., Kumar, K., and Nagel, C., CityGML Application Domain Extension (ADE):
overview of developments, Open Geospatial Data, Softw. Stand., vol. 3, no. 1: 13, (2018),
doi: 10.1186/s40965-018-0055-6.
20. de Laat, R. and van Berlo, L., Integration of BIM and GIS: The Development of the
CityGML GeoBIM Extension, (2011), pp. 211–225.
21. Deng, Y., Cheng, J. C. P., and Anumba, C., Mapping between BIM and 3D GIS in different
levels of detail using schema mediation and instance comparison, Autom. Constr., vol. 67,
pp. 1–21, (2016), doi: 10.1016/j.autcon.2016.03.006.
22. Gröger, G. and Plümer, L., CityGML - Interoperable semantic 3D city models, ISPRS
Journal of Photogrammetry and Remote Sensing, vol. 71. pp. 12–33, (Jul. 2012), doi:
10.1016/j.isprsjprs.2012.04.004.
23. International Organization for Standardization (ISO), ISO 16739-1:2018 Industry
Foundation Classes (IFC) for data sharing in the construction and facility management
industries — Part 1: Data schema. (2018).
24. Pauwels, P., Zhang, S., and Lee, Y.-C., Semantic web technologies in AEC industry: A
literature overview, Autom. Constr., vol. 73, pp. 145–165, (2017), doi:
10.1016/j.autcon.2016.10.003.
25. Open Geospatial Consortium, OGC ® IndoorGML 1.1. (2020).
26. Kim, J. S., Yoo, S. J., and Li, K. J., Integrating IndoorGML and CityGML for indoor space,
vol. 8470. Springer Verlag, (2014).
27. Srivastava, S., Maheshwari, N., and Rajan, K. S., Towards generating semantically-rich
indoorgml data from architectural plans, in International Archives of the Photogrammetry,
Remote Sensing and Spatial Information Sciences - ISPRS Archives, (2018), vol. 42, no. 4,
pp. 591–595, doi: 10.5194/isprs-archives-XLII-4-591-2018.
125
Proceedings of the 9th Linked Data in Architecture and Construction Workshop - LDAC2021
28. Kang, H. K. and Li, K. J., A standard indoor spatial data model - OGC IndoorGML and
implementation approaches, ISPRS Int. J. Geo-Information, vol. 6, no. 4, (2017), doi:
10.3390/ijgi6040116.
29. Kumar, K., Labetski, A., Ohori, K. A., Ledoux, H., and Stoter, J., Harmonising the OGC
standards for the built environment: A CityGML extension for Landinfra, ISPRS Int. J. Geo-
Information, vol. 8, no. 6, (2019), doi: 10.3390/ijgi8060246.
30. OGC, OGC ® Land and Infrastructure Conceptual Model Standard (LandInfra). Paul
Scarponcini, (2016).
31. Kumar, K., Labetski, A., Ohori, K. A., Ledoux, H., and Stoter, J., The LandInfra standard
and its role in solving the BIM-GIS quagmire, Open Geospatial Data, Softw. Stand., vol. 4,
no. 1, (2019), doi: 10.1186/s40965-019-0065-z.
32. Gilbert, T. et al., Built environment data standards and their integration: an analysis of IFC,
CityGML and LandInfra, (2020). doi: https://www.buildingsmart.org/buildingsmart-
international-bsi-and-open-geospatial-consortium-ogc-release-bim-and-gis-integration-
paper/.
33. Donkers, S., Ledoux, H., Zhao, J., and Stoter, J., Automatic conversion of IFC datasets to
geometrically and semantically correct CityGML LOD3 buildings, Trans. GIS, vol. 20, no.
4, pp. 547–569, (2016), doi: 10.1111/tgis.12162.
34. Teo, T. A. and Yu, S. C., The extraction of indoor building information from bim to OGC
indoorgml, in International Archives of the Photogrammetry, Remote Sensing and Spatial
Information Sciences - ISPRS Archives, (2017), vol. 42, no. 4/W2, pp. 167–170, doi:
10.5194/isprs-archives-XLII-4-W2-167-2017.
35. Yu, S.-C. and Teo, T.-A., The Generalization of Bim/Ifc Model for Multi-Scale 3D
Gis/Citygml Models, in Proceedings of the 35th Asian Conference on Remote Sensing, Nay
Pyi Taw, Myanmar, (2014), pp. 27–31.
36. Granholm, L. and Törmä, S., Using Linked Data to facilitate smooth and effective workflow
in a federated model environment, in Proceedings of the 2019 Workshop on Linked Building
Data and Semantic Web Technologies (WLS2019), (2019), pp. 45–52.
37. Hor, A. E. H., Sohn, G., Claudio, P., Jadidi, M., and Afnan, A., A semantic graph database
for BIM-GIS integrated information model for an intelligent urban mobility web application,
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences,
(2018), vol. 4, no. 4, pp. 89–96, doi: 10.5194/isprs-annals-IV-4-89-2018.
38. Hitzler, P., Parsia, B., Patel-schneider, P. F., and Rudolph, S., OWL 2 Web Ontology
Language Primer, W3C Recommendation, (2012). https://www.w3.org/TR/owl2-primer/.
39. Schreiber, G. and Raimond, Y., RDF 1.1 Primer, W3C Working Group Note 24 June 2014,
(2014). https://www.w3.org/TR/rdf11-primer/ (accessed Jul. 22, 2021).
40. Open Geospatial Consortium, OGC GeoSPARQL-A geographic query language for RDF
data. (2012).
41. Koubarakis, M. and Kyzirakos, K., Modeling and Querying Metadata in the Semantic
Sensor Web: The Model stRDF and the Query Language stSPARQL, in The Semantic Web:
Research and Applications, (2010), pp. 425–439.
126