An Ontology based Approach for Assisting Conceptualisation in CAD

Processes

Ewa Grabska

Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, 4 Reymont Str., Krakow, Poland

Keywords: Visual Design, Design Requirement, Diagram, Design Knowledge, Many-Sorted First-Order Logic.

Abstract: This paper continues development of ontological approach to conceptual visual design aided by computer.

Design ideas during the conceptualization phase are externalized by the designer in the form of diagrams on

the monitor screen and automatically transformed by the system into data structures being hyper-graphs.

Hyper-graph structures are combined with logic-based knowledge representation techniques. Different types

(sorts) are used to represent knowledge from diagrams and many-sorted first order languages for their for-

mal specification. The paper is the next attempt to formalize ontology-based knowledge framework for

CAD process. The proposed method is illustrated with an exemplary of design of floor-layouts aided by the

prototype of the System, so called HSSDR (Hyper-graph System Supporting Design and Reasoning).

1 INTRODUCTION

Computer Aided Design (CAD) belongs to well-

established research areas. There are many computa-

tional tools for describing, editing, analyzing, and

evaluating design projects, but the initial conceptual

design phase, mainly based on ontological

knowledge, is very rarely supported by computer

(Yurchyshyna and Zarli, 2009). The application of

ontology in CAD is relatively new and problem ori-

ented.

This paper deals with an ontology based ap-

proach to the conceptual stage of the design process

supported by CAD-system. Different types of design

knowledge essential in visual aspects of a human-

computer dialogue are considered. Initial stages of

designer’s conceptualization are often associated

with sketching. In the proposed approach sketches

are replaced by design drawings in the form of dia-

grams created by the designer on the monitor screen

with the use of a visual editor. The initial drawings

constitute the ﬁrst type of representation storing in-

formation about design solutions. The conceptual

stage of design is based on this representation, which

is important for visual assessment of drawings by

the designer, however not comprehensible for the

computer. Supporting the conceptual design phase

by the computer system requires the data structure

representing the drawings. In the presented approach

they are automatically transformed into attributed

hyper-graph structures. Machine information pro-

cessing in the considered system is based on the

proposed graph representation of design drawings,

which is used by the system to store design

knowledge about drawings and reason about them.

The design knowledge stored in the proposed type of

a graph is translated into logic formulas describing

diagrams. The presented reasoning mechanism

based on these formulas enables the system to check

whether designs satisfy speciﬁed requirements and

constraints. The proposed system makes it possible

not only to extract design knowledge from externali-

zations of designer’s conceptualization but also to

support intelligent decision-making throughout the

conceptual design process.

The presented approach continues development

of knowledge-based decision support design system

(Grabska and Ślusarczyk, 2011). The prototype im-

plementation of this system called the HSSDR (Hy-

per-graph System Supporting Design and Reason-

ing) has been considered in (Grabska et al, 2009).

This paper extends ontological aspects related to

conceptual visual design aided by computer present-

ed in (Grabska, 2011) and simplifies the proposed

earlier top-level ontology for the study of visual

conceptual design process. Our research will be fo-

cused on ontological commitments between design-

er’s conceptualization and different types of

knowledge representation which will be used during

conceptual design process supported by CAD-

272

Grabska E..

An Ontology based Approach for Assisting Conceptualisation in CAD Processes.

DOI: 10.5220/0005080902720279

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2014), pages 272-279

ISBN: 978-989-758-049-9

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

system. Both computer-aided problem solving and

knowledge representation of visual design use struc-

tures of different types (sorts) and many-sorted first

order languages for their formal specification. The

considered in (Grabska, 2011) standard first-order

languages is replaced by more flexible logic lan-

guages in which the concept of sort will be used.

The proposed ontology based approach for as-

sisting conceptualization in CAD process will be

illustrated with an exemplary of design of floor-

layouts supported by system HSSDR.

2 RELATED WORK

Although detailed design and documentation phases

are usually well aided in CAD tools, the initial con-

ceptual design phase is the least supported by the

computer (Minas, 2002). The appropriate computer

representation of knowledge and methods for

knowledge manipulation are needed to construct

knowledge-based design systems (Coyne et al.

1990). These systems are expected to extend their

functionality far over merely creating and editing of

design drawings by the user on the monitor screen.

Following the BIM paradigm (Eastman et al. 2008)

they store all project 3D elements in a central data-

base and are able to generate 2D drawings and 3D

renderings. However, most of these tools do not use

data structures to reﬂect the design knowledge ex-

tracted from initial drawings created by the designer

on the monitor screen during the conceptual design

phase. This knowledge provides a starting point for

design refinement. Therefore, knowledge-based de-

sign systems must be integrated with CAD tools, in

particular with their graphic editors, to facilitate de-

sign process. In other words, we really need to know

much more about how to get computers to have in-

telligent design conversation with us (Lawson,

2001).

The conceptual design phase needs a new ap-

proach based on ontology for assisting designer’s

conceptualization during CAD processes. The pro-

posed in this paper approach provides the automatic

way of generating graph data structure representing

drawings created by the designer on the screen.

These structures have the form of attributed hyper-

graphs which are used quite frequently in

knowledge-based design tools (Schurr et al. 1995) to

facilitate reasoning with logic formulas. The lan-

guage of logic that is the widely used in the theory

of knowledge representation is the language of first-

order formulas (Fagin et al. 1995).

In this paper many-sorted first order languages cor-

respond to attributed hypergraphs. In the languages

arguments and values of functions, and arguments of

predicates may have different sorts (Lifshitz and

Morgenstern, 2008). The many sorted first order

logics are used to semantics and program verifica-

tions, definition of programming languages, data-

bases, computer aided problem solving, and logic

programming and automated deduction.

During the design process aided by computers

drawings being externalization of designer’s concep-

tualisation are seen as thinking aids (Suwa and

Tversky, 1997). The importance of visualization in

design was discussed in (Visser, 2006), while dia-

grammatic conventions allowing for common com-

munication were described in (Booch, et al. 2005).

Another model of inventive designing based on vis-

ual thinking was presented in (Arciszewski, et al.

2009). Visualizing of conceptualizations in the form

of diagrams which facilitate linking mental trans-

formations with physical ones is presented in

(Tversky, 2001). Finding meaning in the reinterpre-

tation of visual representations is discussed in

(Tversky and Suwa, 2009). This paper analyzes the

role of visualization in the process of conceptual

design in the framework of computational ontology.

3 FORMAL MODEL

During the conceptual visual design process aided

by computer the designer has a kind of conversation

with visual objects. This dialogue can be character-

ized as the following cycle: drawing visual objects,

inspecting them, finding new things (e.g., emergent

shapes and/or relations, feedback from the computer

system), and redrawing (Goldschmidt, 1994).

To describe this dialogue the following key

concepts are distinguished (Guarino et al, 2009):

 the domain of discourse being a subset of our

cognitive domain,

 conceptualization, i.e., the objects, concepts,

and other entities that are assumed to exist in

the considered domain of discourse and the re-

lationships that hold among them,

 knowledge based computer system represent-

ing the conceptualization and a logic language

for its explicit specification, and

 with respect to the system observable states of

world which constitute designer’s world.

In the presented approach visual design aided by

computer is our cognitive domain, while designing

floor-layout makes the domain of discourse. In con-

ceptual design process understanding of require-

AnOntologybasedApproachforAssistingConceptualisationinCADProcesses

273

ments based on conceptualizations created in de-

signer’s mind goes together with the visualization of

early design solution (Grabska, 2010). The design-

er’s conversation with visual objects focus on dy-

namic character of the context in which designing

takes place.

It is worth noting that in visual design aided by

computer we need to explicitly specify conceptual-

ization, while conceptualizations are typically im-

plicit in the mind of designer.

Formally, we start with the definition of concep-

tualization stated by Genesereth and Nilsson (Gene-

sereth and Nilsson, 1987).

Definition 1

A conceptualization is a tuple

C = (U, R) where

 U is a set called the domain of discourse, and

 R is a set of relations on U.



In practical application we need to use a language to

refer to the elements of a conceptualization. The

designer usually begins with doing sketches. In other

words he/she uses a visual language. The designer

on the base of the conceptualization can generate an

observable world state. Recently conceptual process

in his/her mind is supported by cognitive tools, such

as computer screen (Tversky and Suwa, 2010). In

this paper to represent the world state, the concept of

visual site will be used (Shimojima, 1996).

A visual site is a drawing along with a surface

on which it is drawn. In general

different surfaces

can be used for drawing, e.g., a sheet of paper or a

monitor screen. Two different drawings on the same

surface determine two different visual sites. In visual

design aided by computer, monitor screen is a basic

visual site on which besides drawing some infor-

mation from computer system can be generated

(Grabska, 2012).

A world is defined as an ordered set of world

states. During the conceptual design phase the world

in the form of a sequence of visual sites is generated

by the designer. In each step of design process for

the same domain of discourse the designer changing

number of elements of the domain of discourse U

and/or relations on it can devise a new conceptual-

ization.

Example 1

Designer’s diagrams presented in the running exam-

ple are made with the use of the prototype system

HSSDR (Grabska et al, 2009). Let us consider the

specialized CAD editor of the HSSDR interface for

designing floor layout composed of polygons which

are placed in an orthogonal grid. These polygons

represent functional areas or rooms. On the base of

ontology the designer visualizes an initial diagram

with three component shown in Figure 1. According

to designer’s convention each line shared by poly-

gons in the diagram is associated with one of two

relations. Lines with door symbol on them represent

the accessibility relation among components, while

continuous lines shared by polygons denote the ad-

jacency relation between them. In our approach the

monitor screen with the diagram shown in Fig. 1

represents the first observable world state w

Figure 1: The diagram corresponding to the conceptualiza-

tion for w

Let C be a conceptualization and W be the set of

world states for C. The tuple (U, W) is called a do-

main space for C. The space fixes variability of the

domain of discourse U with respect to the possible

world states of W.

Definition 2

A conceptual relation



of arity n defined on a

domain space (U, W) is a function



: W → (U

) from the set W into the set of all

n-ary relations on U.



The conceptual relation allows one to extend the

notion of conceptualization for all observable world

states (Guarino et al, 2009).

Definition 3

A conceptualization for W is a triple

C = (U, W,



where

 U is a domain of discourse,

 W is a set of world states, and





is a set of conceptual relations



on the

domain space (U, W).



Example 2

In the next step of design the designer on the base of

the conceptualization for world state w

divides the

area labelled by S into two rooms labelled by Ba and

KEOD2014-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

274

Be. The monitor screen with the diagram shown in

Figure 2 represents the

conceptualization for world

state w

In the presented approach to visual design, draw-

ings of the visual sites from W are the main source

of knowledge about created designs. Mutual location

of polygons is determined by the designer. The sides

of each polygon are ordered clock-wise starting from

the top left-most one. In a diagram only qualitative

coordinates are used, i.e., only relations among

graphical elements (walls) are essential.

Figure 2: The drawing corresponding to the conceptualiza-

tion for w

Drawings are automatically transformed by

HSSDR system into appropriate data graph struc-

tures. Hyper-graphs are used for modelling and

modification of knowledge about drawings

(Grabska, 2011). They can be treated as an extension

of conceptual graphs (Sowa, 1984) with appropriate

structures for local graph transformations. The pro-

posed hyper-graphs have two types of hyper-edges,

called object hyper-edges and relational hyper-

edges. Hyper-edges of the first type correspond to

drawing components and they are labelled by com-

ponent names. Hyper-edges of the second type rep-

resent relations among fragments of components and

can be either directed or non-directed in the case of

symmetric relations. Relational hyper-edges of the

hyper-graph are labelled by names of relations. Ob-

ject hyper-edges are connected with relational hy-

per-edges by means of nodes corresponding to

common fragments of connected drawing compo-

nents.

Example 3

The hyper-graph corresponding to the drawing pre-

sented in Figure 1 is shown in Figure 3. When de-

signing the drawing the designer specifies labels of

components related to room types. For each labelled

design component in the form of a polygon one

component hyper-edge is created. The hyper-graph

shown in Fig. 3 consists of 8 hyper-edges. It has 3

object hyper-edges corresponding to the three poly-

gons being components of the layout and 5 relational

hyper-edges. The relational hyper-edges labelled by

acc (representing accessibility relation) is only one

among relational hyper-edges. The remaining four

relational hyper-edges with label adj represent adja-

cency relation.

Figure 3: The hyper-graph for the diagram in Fig. 1.

The hyper-graph for the drawing corresponding to

the conceptualization for w

is presented in Fig. 4.

Figure 4: The hyper-graph for the diagram in Fig. 2.

As we can see the conceptualization for w

differs

from the conceptualizations for w

both in the num-

bers of components and elements of accessible rela-

tion.

Elements of the domain of discourse have attrib-

utes, like length, area, orientation, colour, etc. In

HSSDR system attributes corresponding to compo-

nents of the drawing are assigned by means of the

attribute function to nodes and object hyper-edges.

Sets of values for particular attributes can be differ-

ent. For instance, values of the area and length are

real numbers, while

values of the orientation belong

to the set {South, West, North, East} of directions.

Let Σ be a ﬁxed alphabet of labels of hyper-edges

and nodes and let A be a set of attributes of hyper

edges and nodes.

Definition 4

An attributed hypergraph over Σ and A is a system

H = (E, V, t, s, lb, att), where

AnOntologybasedApproachforAssistingConceptualisationinCADProcesses

275

 E = E

∪

is a nonempty ﬁnite set of hy-

peredges, where elements of E

, called object

hyperedges, represent drawing components,

while elements of E

, called relational hy-

peredges, represent relations,

 V is a nonempty ﬁnite set of nodes,

 t: E → V* is a mapping assigning sequences

of different target nodes to all hyper-edges,

 s: E

→ V* is a mapping assigning sequences

of different source nodes to relational hyper-

edges,

 lb: E

∪



V → Σ is a labelling function, such that

lb(E)∩lb(V ) =

and

 lb(E

)∩lb(E

) =

 att: E

∪



V → 2

is an attributing function,

where 2

is a set of all subsets of A.



Denote by H(Σ, A) the set of all atoms of attributed

hypergraphs over Σ and A, i.e., the set of all hyper-

edges and nodes.

During the conceptualization in CAD-process

semantic and syntactic information about a drawing

created by the designer is encoded in the hyper-

graph and then translated to ﬁrst-order logic

formulas forming knowledge about design solutions.

Logic formulas are built over a vocabulary T = {S,

F, P} composed of set S of sort symbols, set F of

function symbols and set P of predicate symbols.

With respect to the considered CAD-system two

types of sorts are distinguished. The former

corresponds to objects of domain of discourse and

the latter – the values of attribute functions defined

on the objects.

Let C = (U,W,



) be a conceptualization for W,

and D = D





be indexed family of ranges of

values of attribute functions defined on U.

Definition 5

A many sorted vocabulary of the first order logic is

a triple

T = (S, F, P), where

 S = {U, D } is a set of sort symbols,

 F is a set of elements f such that f is n-ary

function symbol for n > 0 such that

f: s

×s

×…×s

→ s, where s

, s

∊

S, i = 1,…,n,

and f is a constant symbol for n = 0,

 P is a set of m-ary predicate symbols p with

arguments s

×s

×…×s

, s

∊

S, i = 1,…,m.



Let us define the ontological commitment

between the vocabulary of T and a conceptualization

C for W.

Definition 6

Let C = (U,W,



) be a conceptualization for W and

T = (S,F,P) be a many sorted alphabet of the first

order logic.

An ontological commitment between T and C is

a partial function α: T → C satisfying the following

conditions:

 objects of U with respect to the possible world

states of W are assigned to sort symbols,

 objects of D are assigned to constant symbols,

and

 predicate with arguments of U are assigned to

predicate symbols.



Example 4

Let us come back to design floor-layouts shown in

Fig. 1 and Fig. 2 and consider the ontological

commitment between vocabulary and designer’s

conceptualization with respect to the possible world

states of W, i.e., represented by visual sites along

with designs drawings. Shapes which represent

rooms, walls and doors correspond to elements of

the objects of U, whereas the set  of real numbers

and the set of directions, i.e.,{South, West, North,

East} – to values of D. Function symbols such as

area and length, and directions with arguments of U

as well as the ranges of values being the set of 

and the set {South, West, North, East} correspond to

attributes of objects. Predicate symbols such as acc

and adj determine relations between rooms.

Since HSSDR system deals with computer

representation of drawings, the explicit specification

must be formal, i.e., the expressions must be

computer readable. We assume that our language is

a many sorted first-order logical language. The

semantics of many-sorted first-order formulas uses

relational structures based on knowledge encoded in

the considered hyper-graphs. A relational structure

consists of domains of different types (sorts) and a

way of associating with each of elements of the

vocabulary T corresponding entities over the domain

(Ślusarczyk, 2011)

Definition 7

A relational T-structure L consists of:

 a domain dom(L) = dom(L

)



dom(L

), where

dom(L

) and dom(L

) contain domains for

objects of domain of discourse U and for

attribute values of D, respectively,

 an assignment c



dom(L

) to each constant

symbol c of U,

 an assignment c



dom(L

) to each constant

symbol c of D,

KEOD2014-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

276

 an assignment n-ary function

 f

: dom(L)

domL

to each n-ary function

symbols f



F, and

 anassignment

n‐ary

predicate

dom(L)



toeach

n–ary

predicate symbol p



P.



In the proposed visual design approach the

T-relational structure L contains two domains:

 dom(L

) 

(Σ, A) is a set of component hy-

per-edges E

and a set of hyper-graph nodes

V, and

 dom(L

) is an indexed family of sets

 D =





∊

, where

 A is a set of attribute functions defined on

 E

and V and for each a

∊

A, D

is the range

 of attribute values of function a in D.

Relations between design components presented in

the drawing are specified between fragments of

these components, which correspond to hyper-graph

nodes. The interpretation of each relation is the hy-

per-edge relation of the hyper-graph such that there

is a relational hyper-edge coming from a sequence

of nodes of at least one component hyper-edge and

coming into a sequence of nodes of other component

hyper-edges. Functions determine attribute values

for components hyper-edges and nodes.

The next step to define the formal semantics of

formulas is a specification of an interpretation of

variables. A valuation on a structure L is a function

from variables to elements of dom(L). Given a rela-

tional structure L with a valuation ω on L, (L,ω) |= φ

denotes that a formula φ is true in L under the valua-

tion ω.

Example 5

In the considered example two names of relations

are used: acc and adj. For a given relational struc-

ture L with a valuation ω on L the relation assigned

to the name acc is defined as follows:

(L,ω) |= acc(x

) iff ∃v

 

V such that ω(x

) =

, ω(x

)=v

, v



t(e

),v



t(e

), where e



and

∃ e



such that v

 

t(e

), lb(e

) = acc, i.e.,

there exist two nodes being valuation of variables x

and x

, respectively, and assigned to two different

object hyper-edges and to the same relational hy-

peredge labelled acc.

Fig. 5 presents a subgraph of the hypergraph in

Fig. 3 representing accessibility of rooms. The defi-

nition of the adjacency relation (adj) differs from the

definition of accessibility relation (acc) only in the

label of a relational hyper-edge (see: Fig. 6).

Figure 5. A subgraph of the hypergraph in Fig. 3 repre-

senting accessibility of rooms.

Figure 6. A subgraph of the hypergraph in Fig. 3 repre-

senting adjacency of rooms.

Atomic sentences obtained on the basis of the rela-

tions which hold between components of ﬂoor lay-

outs constitute syntactic knowledge about the solu-

tions being the result of a design process. In the

running example the knowledge related to the lay-

outs contains sentences concerning direct accessibil-

ity, and adjacency between rooms. The obtained

logical language composed of formulas inferred

from hyper-graphs enables HSSDR system to reason

about compatibility of designs with constraints

speciﬁed as a part of general design knowledge.

Rules of the general design knowledge describe de-

sign standards like architectural norms, ﬁre regula-

tions, etc.

Additionally, there exists the possibility to speci-

fy designer’s own requirements in the form of logic

formulas using the rule editor being a part of the

design interface. Designer’s requirement can be as

follows:





room area(x)



15. For the layouts

drawn by the designer on an orthogonal grid the sys-

tem automatically calculates the values of the attrib-

ute specifying the area of rooms. Then the reasoning

module can check the agreement between the pro-

posed layout and designer’s requirement.

AnOntologybasedApproachforAssistingConceptualisationinCADProcesses

277

4 CONCLUSION

The separation of designing from making and the

increased importance of the drawing characterise the

modern design process. The major work of initial

conceptual design in CAD is done through a human-

computer dialogue. This paper proposes an ontology

based approach for assisting designer’s conceptuali-

sation in CAD processes. The difficulty lies in the

distinction between the logical notion of model and

the ontological notion of possible worlds (Guarino et

al, 2009). The former is described by abstract struc-

tures, while the letter is represented by observed

states of affairs. The number of world states, i.e., the

number of visual sites, depends mainly on creativity

of the designer.

The role of the logical model is to assign rela-

tional structures to vocabulary elements. Graph can

be combined with the most logic-based knowledge

representation techniques, where knowledge is rep-

resented explicitly by symbolic terms and reasoning

is the manipulation of these terms. In the proposed

approach the semantics of logical formulas uses rela-

tional structures based on hyper-graphs.

It is known that the degree to which an ontology

specifies a conceptualization depends on the rich-

ness both of the domain of discourse and the vo-

cabulary, and logic language expressiveness. In the

considered paper many sorted logic language is used

to express properties of attributed hyper-graphs of

different sorts.

The proposed ontological approach provides in-

sight in how humans aided by computer solve visu-

al design problems. In our future research we shall

consider a new example ontology focusing attention

on influence of computer technology on visual de-

sign creativity.

REFERENCES

Yurchyshyna, A., Zarli, A., 2009. An Ontology-based

Approach for Formalisation and Semantic Organiza-

tion of Conformance Requirements in Construction. In

International Research Journal Automation in Con-

struction. Volume 18. Issue 8, pp. 1084-1098.

Grabska, E., Slusarczyk, G., 2011. Knowledge and reason-

ing in design systems. In Automation in Construction

22, pp. 927–934.

Grabska, E., et al., 2009. Hypergraph system supporting

design and reasoning. In Intelligent Computing in En-

gineering, 20th EG-ICE International Workshop, pp.

134–141.

Grabska, E., 2011. Computer Aided Conceptual Visual

Design based on Ontology, In KEOD, 3

Internation-

al Conference on Knowledge Engineering and Ontol-

ogy Development, pp. 396–399.

Minas, M., 2002. Concepts and Realization of a Diagram

Editor Generator Based on Hypergraph Transfor-

mation. In Science of Computer Programming 44,

2002, pp.157–180.

Coyne, R. D., et al. 1990, Knowledge based design sys-

tems, Addison-Wesley Publishing Company, 1990.

Guarino, N., et al. 2009. What Is an Ontology. Handbook

on Ontologies. Springer, Heildelberg.

Eastman, Ch., et al. 2008. BIM Handbook: A Guide to

Building Information Modeling for Owners, Manag-

ers, Designers, Engineers and Contractors, Wiley.

Lawson, B., 2001, How designers think, Architectural

Press.

Grabska, E., 2010. Visual design with the use of graph-

based data structure. eWork and e-business in Archi-

tecture, Engineering and Construction, Taylor and

Francis Group. London, pp. 209–214.

Tversky, B., Suwa, M., 2009. Thinking with sketches. In

Tools for innovation. Oxford University Press.

Markman, A. B. & Wood, K. L., (Eds.), Tools for innova-

tion, Oxford.

Schurr, A., et al. 1995. Graph grammar engineering with

PROGRES, In LNCS, 989, 5th European Software

Engineering Conference (ESEC95), Springer-Verlag,

Berlin, pp. 219–234.

Visser, W., 2006. The cognitive artifacts of designing,

Erlbaum L. Associates, Mahwah, NJ.

Booch, G., et al. 2005. The uniﬁed modeling language

user guide. Addison-Wesley, NJ.

Arciszewski, T., et al. 2009. Visual Thinking in Inventive

Design: Three Perspectives. In Soft Computing in Civil

and Structural Engineering. Saxe-Coburg

Publications, pp. 179 -202.

Tversky, B., 2001. Spatial schemas in depictions. In

Spatial schemas and abstract thought, MIT Press.

Ware, C., 2008. Visual thinking for design, Elsevier.

Goldschmidt, G., 1994. On visual design thinking. In

Design Studies 15, pp.158–174.

Fagin, R., et al. 1995. Reasoning About Knowledge, MIT

Press, Cambridge.

Lifschitz V., Morgenstern L., 2008, Knowledge

Representation and Classical Logic, Handbook of

Knowledge Representation, van Harmelen F.,

Lifschitz V., Porter B. (Eds), Elsevier.

Suwa, M., Tversky, B., 1997. What architects and students

perceive in their sketches: A protocol analysis. In

Design Studies 18, pp. 385–403.

Genesereth M. R., Nilsson N.J., 1987. Logical Foundation

of Artificial Intelligence.

Morgan Kaufmann. Los

Altos. CA.

Grabska E., 2012. Towards a Formal Model of Visual

Design, In Advances in Intelligent and Soft

Computing, Systems Interaction: Backgrounds and

Applications 2, pp. 135–147.

Barwise J., Seligman J., 1997. The Logic of Distributed

Systems, Cambridge University Press.

KEOD2014-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

278

Shimojima A., 1996. Operational Constraints in Dia-

grammatic Reasoning. In Logical Reasoning with Di-

agrams. Oxford University Press, pp. 27–48.

Lawson, B., 2001. How designers think: the design

process demystified. Butterworth Architecture.

Oxford.

Grabska, E., et al. 2008. Visual Design and Reasoning

with the Use of Hypergraph Transformations. In

ECEASST 10, pp. 1–15.

Sowa, J. F., 1984. Conceptual Structures: Information

Processing in Mind and Machine. Addison-Wesley.

Ślusarczyk, G., 2011. Visual design with the use of

hierarchical hypergraphs. (in Polish). Studia

Informatica. Silesia University of Technology Press.

AnOntologybasedApproachforAssistingConceptualisationinCADProcesses

279