An Improved Approach for Effective Describing Geometric Data in

ifcOWL through WKT High Order Expressions

Dongming Guo

a

, Erling Onstein

b

and Angela Daniela La Rosa

c

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.

1 INTRODUCTION

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.

a

https://orcid.org/0000-0001-5357-8410

b

https://orcid.org/0000-0002-5447-7563

c

https://orcid.org/0000-0002-5739-6005

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

Copyright

c

2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

229

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

interoperability.

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.

2 RELATED WORK

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

230

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

coordinates.

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.

2017)

.

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

231

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

facets.

3 AN IMPROVED WKT

REPRESENTATION

APPROACH IN IFCOWL

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

problems:

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

expressions?

3.1 Which Information Will Be Lost

When using WKT Higher Order

Geometrical Expressions in

ifcOWL?

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

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(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

IFC.

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

233

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

#38=IfcShapeRepresentation(#11,'Axis','Curve2D',(

#37)) and the related geometric information are

retained and expressed as a LINESTRING WKT. The

#47=IfcShapeRepresentation(#11,'Body','SweptSolid

',(#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

#61=IfcShapeRepresentation(#11,'Body','SweptSolid

',(#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.

4 ANALYSES AND DISCUSSIONS

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

234

(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.

5 CONCLUSIONS

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

235

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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