An Improved Approach for Effective Describing Geometric Data in
ifcOWL through WKT High Order Expressions
Dongming Guo
, Erling Onstein
and Angela Daniela La Rosa
Department of Manufacturing and Civil Engineering, Norwegian University of Science and Technology, Gjovik, Norway
Keywords: ifcOWL, Well-Known Text (WKT) Expressions, IFC Schema, Geometry Data, Shape Representation.
Abstract: Building Information Models (BIM) are considered as building digital representations, including
comprehensive geometric and non-geometric information. For improving BIM interoperability, the semantic
related technologies have been the one of main approaches for processing BIM data. Currently, ifcOWL is a
recommended Web Ontology Language (OWL) representation of the Industry Foundation Classes (IFC)
schema. When BIM geometric data is translated into ifcOWL representations, the excessive number of triples
will be produced, and the generated Resource Description Framework (RDF) file will also be extremely bigger
than the IFC original file. For generating concise geometric representation in Semantic Web context, Well-
known text (WKT) has been widely used to describe BIM geometry data in ifcOWL. However, to avoid losing
semantic information, only some simple pre-existing WKT expressions (Point or LineString) are used to
describe BIM geometric aggregated data in semantics context. For solving this issue, we propose an improved
approach that can represent BIM geometric data in ifcOWL ontology through WKT high order expressions.
This representation can not only take full advantage of pre-existing WKT expressions to generate a more
concise RDF representation, but also reduce the loss of semantic information.
Recent years, Building Information Model (BIM) is
widely used in Architecture, Engineering and
Construction (AEC) industry as digital
representations and repository of building
information (Zhao 2017). To facilitate information
sharing and interoperability in AEC industry, a data
model with neutral platform and open file format,
Industry Foundation Classes (IFC) (ISO 2013), is
developed by buildingSMART organization. Along
with the spread and development of IFC, IFC has
already been a common data schema and try to cover
the entire AEC industry (Laakso and Kiviniemi
2012). BIM cases based on IFC schema can contain
geometry information of all building elements, such
as 3D shape and the enclosed spaces, and non-
geometric semantic information, such as the
properties of the elements and the relationships
between them.
Although IFC shows certain capabilities of
implementing information sharing/exchange and
improving interoperability in AEC industry, semantic
clarity is not achieved in IFC that may result in non-
efficient data exchange among different
applications/stakeholders (Zhong et al. 2019).
Additionally, semantic web and linked data
technologies also promote the presentation of BIM
data in a comprehensible form, especially in a
machine-understandable form (ontological form). So,
a recommended Web Ontology Language (OWL)
representation of the IFC schema, ifcOWL, is also
developed and standardized by buildingSMART
(buildingSMART 2019a). The ifcOWL has been an
open ontology for representing building data in
Resource Description Framework (RDF) format. It
also accelerates to process BIM data by semantic
approaches in diversified engineering applications
(Zhong et al. 2019).
Geometry data in BIM is one of important parts of
building data, and the converting building geometry
Guo, D., Onstein, E. and Rosa, A.
An Improved Approach for Effective Describing Geometric Data in ifcOWL through WKT High Order Expressions.
DOI: 10.5220/0010532302290236
In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2021), pages 229-236
ISBN: 978-989-758-503-6
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
data into RDF format also needs to be considered for
supporting related geometric processing and
applications in Semantic Web context. Currently,
most research mainly focuses on non-geometric data,
and the description of construction-related geometric
data in Semantic Web context is still a challenge and
the uniform or general recommendation has not been
achieved (Wagner et al. 2020). Hence, in the semantic
web context, the processing of geometry data
generally requires special attentions because diverse
geometry descriptions may be used in different
processing approaches based on specialized geometry
ontologies (McGlinn et al. 2019). Wagner et al.
(Wagner et al. 2020) summarized and analyzed
approaches of geometry descriptions in Semantic
Web context into four groups and evaluated the four
groups with six aspects: semantic expressivity,
flexibility, conciseness, simplicity, support,
portability and extensibility. In their evaluations, the
third group (using a Semantic Web approach for
linking and storing geometry descriptions and other
technologies for expressing geometry content and
structure) showed out the more advantages in six
aspects, in which Well-Known-Text(WKT) has been
the most widely used to express geometry data as
RDF literals (Wagner et al. 2020). WKT can
represent several geometric objects, such as Point,
MultiPoint, LineString, MultiLineString, Polygon,
MultiPolygon, etc. However, in this kind of
approaches, only some limited pre-existing WKT
expressions are used in Semantic Web context to
express the limited geometric data, because semantic
information will be lost when some WKT high order
expressions (e.g. MultiLineString, Polygon,
MultiPolygon) are introduced to express BIM
geometry data. For solving this issue, we propose an
improved approach for effective describing
geometric data in ifcOWL ontology through WKT.
This representation can not only take full advantage
of pre-existing WKT expressions to generate amore
concise semantic representation, but also reduce the
loss of semantic information. Our approach can be
considered as an initial endeavour to explore the use
of high order WKT to express building geometry data
in OWL/RDF-environments, and possibly as one of
feasible approaches for improving GIS and BIM
In this paper, we mainly focus on the improving
the representation of geometry data in ifcOWL
ontology. We introduce a new WKT representation
approach for BIM geometry data in ifcOWL
ontology. In the section 2, we briefly review the
related work about RDF representation approaches of
BIM geometry data in ifcOWL ontology. After that,
we analyze the possible semantic loss in WKT
representation with pre-existing WKT expressions in
section 3. For solving this problem, we also introduce
our approach in section 3. Section 4 shows our
analyses and discussions about our approach. Finally,
we make a brief conclusion in section 5.
For different engineering applications and geometric
representations, some novel geometry ontologies
have been developed. For example, Building
Topology Ontology (BOT) can capture the
topological logical information of a building structure
and elements (Rasmussen et al. 2017). The boundary
representation OntoBREP ontology can use a
mathematical model to describe geometric properties
of objects, including topological entities (e.g. solids,
shells, wires, edges) and geometric entities (e.g.
points, curves, surfaces) (Perzylo et al. 2015). The
GEOM ontology aims at capturing geometry from
different sources with minimal loss of expressiveness
(RDF.Ltd. 2012). In this paper, we only focus on
discussing the related research about geometry
representation in ifcOWL ontology.
Beetz et al. (Jakob Beetz 2007) pointed out that an
RDF representation of geometric information that
contained little semantic information was fairly
inefficient and provided little additional value when
it cannot be used in a logical inference/reasoning
process. The logic inference and semantic search
functionalities are important features provided by
OWL and desirable for AEC industry. So, the design
of RDF representation of geometric data is limited by
certain notations (e.g. compatible with Description
logics (DL)) or data types. For example, RDF terms
rdf:list - rdf:first - rdf:rest (Brickley and Guha 2014)
cannot be used in ifcOWL ontology to represent
ordered aggregation data types of BIM because the
generated ontology based on these RDF terms cannot
be used for logical inference (Pauwels et al. 2017).
In all data types for representing geometric
information, aggregation data types (e.g. ordered lists
of point in Cartesian point, ordered lists of Cartesian
points in polylines) are commonly adopted in IFC
schema. How to effectively represent these geometric
aggregate data types in OWL ontology has become
one of the main research challenges. Translating the
LIST data types in IFC schema into OWL expression
has been discussed by Pauwels et al. (Pauwels et al.
2017) and de Farias et al. (de Farias, Roxin, and
Nicolle 2015). In these translation approaches,
ordered lists or sequences have been received major
GISTAM 2021 - 7th International Conference on Geographical Information Systems Theory, Applications and Management
attentions because RDF data based on a triple
structure (subject–predicate–object) represents
ordered aggregated data types as fairly complex
expressions (Pauwels and Terkaj 2016; Hoang and
Törmä 2015). A typical example was illustrated in
Figure 1, in which a Cartesian point in IFC schema
was converted into ifcOWL. The conversion was
recommended by buildingSMART and implemented
by Pauwels et al (Pauwels et al. 2020). It is clear in
Figure 1 that several triples are required to represent
a cartesian points (an ordered list), including triples
for expressing connection relationships of axes
(list:hasNext) and necessary triples for expressing the
semantic information of Cartesian point and
coordinate values (list:hasContents,
express:hasDouble). This converted approach caused
the converted RDF file to be much larger than the
original IFC file. (Hoang and Törmä 2015).
Figure 1: An example for converting an IfcCartesianPoint
((10.0, 0.0, -10.0)) into the ifcOWL representation, based
on the converting approach in (Pauwels et al. 2020).
When the expression of Cartesian coordinate
values was not changed in RDF, the changing the
expression of connection relationships of axes may be
an alternative approach for improving the
representation of Cartesian point in ifcOWL. It
generally resulted in customized new concepts in
ifcOWL ontology (Pauwels et al. 2017). In this kind
of approaches, new properties were created to point
directly to each item in a list of two or three
coordinates and then to distinguish between 2D and
3D IfcCartesianPoint concepts (Pauwels et al. 2017),
shown in Figure 2, in which an instance of a Cartesian
point had three connected properties to express 3D
When the expression of Cartesian coordinate
values was also changed and combined with the
semantic information of coordinate axis of a
Cartesian point, a more concise representation was
proposed and illustrated in Figure 3, in which three
triples were required for representing three coordinate
values and 3D coordinate properties of a Cartesian
point (Pauwels et al. 2017). The new data type
properties were required to be defined in this
representation and the cons and pros of this approach
was discussed in ref. (Pauwels et al. 2017). Although
this is a concise and simple representation, a
Cartesian point in IFC schema was still converted into
three triples, which inevitably leaded to the size
increase of a converted file.
Figure 2: A representation of an IfcCartesianPoint ((10.0,
0.0, -10.0)) in ref. (Pauwels et al. 2017).
Figure 3: A representation of an IfcCartesianPoint ((10.0,
0.0, -10.0)), modified procedure 3b in
(Pauwels et al.
Figure 4: A representation of an ifc:CartesianPoint using
the WKT approach.
Currently, it is accepted that using pre-existing
WKT represents the BIM geometry data in ifcOWL
and generates a concise RDF representation (Pauwels
An Improved Approach for Effective Describing Geometric Data in ifcOWL through WKT High Order Expressions
et al. 2017, McGlinn et al. 2019). For example, a
POINT WKT string was adopted to represent a
Cartesian point in IFC schema, shown in Figure 4. In
this approach, only one triple in RDF can express an
instance of IfcCartesianPoint in IFC schema.
Similarly, the new formal definitions of data types
were required in this approach. It was tested that the
number of RDF triples can be decimated in several
IFC4 cases after applying WKT to express
triangulated geometries and Cartesian points in IFC4
(Pauwels et al. 2017). Additionally, WKT has been
defined in Simple Feature Access (John R. Herring.
2011) and the re-use of existing vocabularies of WKT
agreements was also recommended by W3C’s Linked
Data Best Practices (Bernadette et al. 2014).
However, WKT expressions are limited to represent
IFC schema, because WKT has been mainly applied
in the geospatial domain and only focuses on
geometrical information, non-geometric concepts in
IFC schema cannot be represented by WKT.
Furthermore, some special geometries in IFC schema
that are not used in the geospatial domain cannot be
directly represented by WKT.
Additionally, using some powerful WKT
expressions to directly represent BIM geometric
information will lose semantic information. For
example, the geometric information of a wall
containing an opening for a window can be expressed
by WKT PolyhedralSurface Z, shown in Figure 5.
This WKT expression (PolyhedralSurface Z) was
largely compressed the number of RDF triples for
representing the geometry data of the wall, whereas
the loss of semantic information was not avoided in
this representation (Pauwels et al. 2017). The other
improvement approach may be to design new WKT
expressions according to the IFC schema. However,
the introducing new WKT expressions in ifcOWL are
not recommended by Pauwels et al. (Pauwels et al.
2017), because the new WKT expressions require the
additional and necessary effort to make data
reasoners/query engines include and understand these
expression strings. Currently, for achieving concise
RDF representation and retaining semantic
information, the geometric descriptions of products in
IFC schema are commonly changed to apply to WKT
expressions, such as WKT triangulated boundary
representation, in which a solid surface is segmented
into multiple triangular facets, and then WKT Point
expression is used to record the vertices of triangular
To overcome the limitation of pre-existing WKT
expressions for representing IFC geometry data in
ifcOWL ontology, we develop a new WKT
representing approach that can further utilize pre-
existing WKT geometry primitives and avoid the loss
of sematic information. Here, we mainly explore two
1. Which information will be lost when using
WKT high order geometrical expressions in ifcOWL,
such as PolyhedralSurface Z?
2. How to try to avoid the loss of semantic
information when using WKT high order
3.1 Which Information Will Be Lost
When using WKT Higher Order
Geometrical Expressions in
We take the case in Figure 5 as an example to discuss
this problem. WKT expressions commonly use global
spatial reference systems (the world coordinate
system) (John R. Herring. 2011). However, a product
defined in IFC schema generally has the relative
coordinates/placement in relation to the placement of
another product (BuildingSMART 2019b). So, the
relative coordinates must be converted into the world
coordinates in WKT expressions. In the Figure 5 (c),
the first nine lines show the information about relative
placement, and this kind of information can be used
to convert the local placements/coordinates into
world coordinates in WKT, including the following
the segments #50-#52. When all products/elements
are defined with world coordinates, the relative
relationships of products in IFC can be implicitly
contained in world coordinates of products. So, these
information about IfcLocalPlacement and the related
information cannot be considered to be lost.
GISTAM 2021 - 7th International Conference on Geographical Information Systems Theory, Applications and Management
(a) A wall with an opening element
(b) The WKT description of the wall
(c) The subset of the geometry information of the wall in
Figure 5: A case about using WKT to express a wall with
an opening element provided in ref. (Pauwels et al. 2017).
The following segment
#48=IfcProductDefinitionShape ($,$,(#38,#47))
defines two geometric shape representations of this
product, which are a 2D representation (#38) and a
“Body” 3D model (#47). The expression of Figure
5(b) only contains the 3D geometry information,
excluding the 2D geometric information. Although
the 2D geometric information can be deduced through
3D geometry information and a corresponding 3D
engine, the part 2D semantic information are indeed
lost, such as the semantic information of “Axis” and
“Curve2D” and data value, which are retained in
converting approaches recommended by
buildingSMART (buildingSMART 2019a; Pauwels
and Terkaj 2016). Additionally, these semantic
descriptions are meaningless even if they are
compulsively kept in the ifcOWL ontology, because
these semantic descriptions have lost the direct
relevant geometric data value.
The geometric information of “Body” solid model
(#47) and the following geometric related
descriptions have been expressed in Figure 5(b) with
the world coordinates. After that, the opening
element, described in IfcOpeningElement in #63, has
the relative placement information and “Body”
descriptions, which are also expressed in the WKT
expression of the figure 5(b). However, the property
IfcIdentifier of the IfcOpeningElement is lost in
Figure 5(b), which can be used to link with the
following lines: #64(IfcRelVoidsElement),
#65(IfcWindow) and #66(IfcRelFillsElement).
Moreover, because the geometric data of an opening
element is merged into the whole geometric
description of the wall, the other semantic
information of an opening element can be hardly
effectively correlated with the geometric data of an
opening element in ifcOWL ontology, especially
when multiple opening elements exist in a product.
Additionally, the current converting approaches
in ref. (buildingSMART 2019a; Pauwels and Terkaj
2016) keep all semantic information about
IfcCartesianPoint and every IfcCartesianPoint entity
can be independently reused or linked with other
ontologies. However, the semantic and geometric
information about IfcCartesianPoint entities have
been combined into an RDF literal in Figure 5(b),
where every IfcCartesianPoint entity cannot be used
independently without parsing the RDF literal. The
combination of semantic information of
IfcCartesianPoint entities can be viewed as the cost
and key of compression of RDF, when using WKT
expressions in ifcOWL.
An Improved Approach for Effective Describing Geometric Data in ifcOWL through WKT High Order Expressions
3.2 How to Try to Avoid the Loss of
Semantic Information in WKT
High Order Expressions?
Based on the above analyses, several semantic
information may be lost, mainly including 2D
representation and the related semantic information of
the opening element, while some information may be
transferred from explicit expressions to implicit
expressions, such as the relative relationships among
products. The main reason of losing information is that
the geometric representation is over-concentrated. To
avoid losing the semantic information and introducing
high order WKT expressions, we propose a new
approach that can use pre-existing WKT expressions
(including WKT high order geometric expressions) to
be suitable for ifcOWL ontology. The main idea is to
use multiple WKT expressions to describe geometric
information of a product according to its descriptions
in IFC.
The IfcShapeRepresentation in IFC schema can
describe different geometric representations of a
product or different product components
(BuildingSMART 2019b). So, in our approach, basic
WKT point and line expressions will continue to be
used, such as expressing the position information of
IfcSite or IfcBuidling. Additionally, an important
criterion in our approach is to use one appropriate
WKT expression for every IfcShapeRepresentation in
IFC schema if the geometric information of the
products can be expressed by WKT. Except the
geometric information, the other information in IFC,
including semantic descriptions, properties and
relationships, can still be converted into RDF by
approaches recommended by buildingSMART
(buildingSMART 2019a; Pauwels and Terkaj 2016).
In our approach, high order WKT expressions can be
considered to be simplified to adapt to IFC schema,
because expressing a complex structure of a product
can require several IfcShapeRepresentation instances
in IFC schema and every IfcShapeRepresentation
instance has a WKT expression in our approach. That
means multiple WKT expressions can split the
expression of the complex structure of a product and
the split structure can also simplify complex
expression in WKT. The semantic relationships
among the several WKT expressions of a product are
the semantic relationships among corresponding
IfcShapeReresentation instances in IFC schema.
We still use the case in Figure 5 to explain our
proposal. The case in Figure 5 only used one WKT
expression to represent geometric information of the
wall and it will inevitably lead to the loss of semantic
information. In our approach, the 2D geometric
information of the wall in
#37)) and the related geometric information are
retained and expressed as a LINESTRING WKT. The
',(#46)) and the following lines until #43 segment are
still expressed as PolyhedralSurface Z. Because there
is an opening in the wall, an extra WKT expression
PolyhedralSurface Z is needed to express the
',(#60)) and following related geometric information.
So, three WKT expressions are required to describe
the geometric information of the wall in Figure 5 in
our proposal. Our approach can avoid the loss of
semantic information and generate a concise RDF
representation. The results of our approach are show
in Figure 6, in which some spaces are added for
improving legibility in WKT and they can be
removed to further condense. It is noted that we only
change the expression of geometry information of a
product in our approach. The other semantic
information of a product and relationships of different
components of a product are retained into RDF to
avoid the loss of semantic information.
In our approach, every IfcShapeRepresentation
instance is specified a corresponding WKT expression
to describe related geometric information. Although
the WKT expression form of IFC geometric
information is different with IFC schema, the structure
of the WTK geometry expression in ifcOWL ontology
is similar with IFC schema in our approach. The
geometric data of every IfcShapeRepresentation
instance is converted into WKT, while the other
semantic information still be retained in an
inst:IfcShapeRepresentation instance in ifcOWL. In
this way, properties of a product can be easy to be
linked with the related shape representations.
Furthermore, that all shape representations of a
product are kept in ifcOWL ontology can lessen the
loss of semantic information. Meanwhile, the
relationships of multiple WKT expressions of a
product can be clearly expressed in ifcOWL based on
their relationships in IFC. Additionally, in engineering
applications, the required WKT expressions can be
independently extracted. For example, when
comparing the opening element size with the window
size, WKT expressions of the opening element and the
window can be separately extracted and compared.
Generally, WKT can represent some complex
geometric objects, such as using PolyhedralSurface Z
GISTAM 2021 - 7th International Conference on Geographical Information Systems Theory, Applications and Management
(a) WKT LineString expression for 2D
(b) WKT PolyhedralSurface Z expression for “SweptSolid”
(c) WKT PolyhedralSurface Z expression for “SweptSolid”
Figure 6: The new WKT representation approach for a wall
with an opening element.
to express 3D polyhedral surface with holes
(openings) and using Polygon to express 2D polygon
with interior linear rings etc. However, IFC schema
adopts multiple IfcShapeRepresentation entities to
respectively describe polyhedral surface and opening
elements of a product. So, WKT PolyhedralSurface Z
or Polygon used in our approach (without holes or
interior linear rings, because holes and interior linear
rings are expressed in other WKT expressions) will
be simpler than used in geospatial domain.
Furthermore, our approach doesn’t require to change
the definitions of pre-exist WKT expressions in RDF
and may use these high order WKT expressions in
ifcOWL ontology.
In terms of the number of triples in RDF, our
approach has more concise RDF representation than
ifcOWL ontology (buildingSMART 2019a) and
conservative WKT serialization proposed by Pauwels
et al. (Pauwels et al. 2017), because some high order
WKT expressions can be used in our approach, which
can combine multiple Cartesian points into one
expression. The results of triple count for expressing
the wall contained a window in three approach are
shown in Figure 7.
However, curves cannot be serialized in WKT that
can only describe points, linear-segments, polygon
and the high order combinations of them in 2D or 3D
(John R. Herring. 2011). The construction-related
geometric information contained curves cannot be
expressed by WKT, which limits applications of
WKT in ifcOWL. Meanwhile, it is also a limitation of
our approach. Additionally, when using WKT to
expression geometric information in our approach,
some extra calculations are necessary for the
converting from IFC schema into RDF, such as the
converting calculation from relative coordinates to
world coordinates and some geometry shape
expressing calculations from IFC schema to high
order WKT expressions, etc. Additionally, the
converting IFC geometry data into WKT expressions
may be a complex task, because a whole building can
have hundreds/thousands of IfcShapeRepresentation
entities, and the converting task is hardly
implemented manually. The curve expression in
WKT and the automatic converting program (from
IFC schema to WKT expressions) need to be further
researched. If these issues will be overcome,
geometric data in building/construction and
geospatial domain can be expressed in WKT, and
WKT may be a feasible approach for improving GIS
and BIM interoperability.
In this paper, a new expression approach is proposed
for using WKT expressions in ifcOWL. It cannot only
provide concise RDF representation with high order
WKT expressions, but also avoid the loss of semantic
information in ifcOWL. In our approach, an
appropriate WKT expression is used for every
IfcShapeRepresentation instance in IFC schema if the
An Improved Approach for Effective Describing Geometric Data in ifcOWL through WKT High Order Expressions
geometric information of a product can be expressed
by WKT. It means that every IfcShapeRepresentation
instance has its independent geometric expression
and the related property semantic information of
every IfcShapeRepresentation instance can be linked
with its geometric expression. Based on geometry
descriptions in IFC schema, multiple WKT
expressions may be used to express the geometric
information of a product. So, WKT high order
expressions can be used to generate the more concise
RDF representation in our approach. Because the
WKT high order expressions are used, the limitations
of WKT also become the limitations of our approach.
Figure 7: Triple counts for the ifcOWL, conservative WKT
representations and our approach.
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