CONSTRUCTING WEB ONTOLOGIES INFORMED BY

SEMANTIC ANALYSIS METHOD

Júlio Cesar dos Reis

Department of Information Systems, Institute of Computing, University of Campinas

and Center for Information Technology Renato Archer, Campinas, São Paulo, Brazil

Rodrigo Bonacin

Center for Information Technology Renato Archer, Rodovia Dom Pedro I, km 143,6

13069-901, Campinas, São Paulo, Brazil

Maria Cecilia Calani Baranauskas

Department of Information Systems, Institute of Computing, University of Campinas

Av. Albert Einstein, 1251, 13083-970, Campinas-SP, Brazil

Keywords: Organizational Semiotics, Semantic Analysis Method, Web Ontology Language, Semantic Web.

Abstract: In the context of the Semantic Web (SW) research, recent proposals have explored new approaches for a

more precise representation of the meanings. These proposals attempt to model the information in a more

adequate way, and, at the same time to be compatible with the SW standards. This paper proposes heuristics

for deriving an initial Web ontology (WO) from Ontology Charts (OCs) produced by the Semantic Analysis

Method (SAM).

1 INTRODUCTION

There is a growing need for methods, techniques and

tools to better represent the semantic aspects of the

information available in Web systems. The first

initiatives taken by Berners-Lee et al. (2001) already

aimed at creating a Web that also takes into account

the meanings of information and not just its structure

and protocols. Nevertheless, recent studies point out

that there are still various limitations and problems

regarding technologies coming from the SW

initiative (e.g., Reis et al., 2010).

Modelling approaches for WOs that uses the

(SAM) (Liu, 2000) as a starting point may provide a

more precise representation of the semantics. This

approach proposed here enables to incorporate into

SW ontologies, concerns and possible

representations arising from a Semiotic perspective

(Reis et al., 2010).

Assuming that the Semiotic approach contributes

with improvements in business modelling, it is

plausible to have both: the Organizational Semiotic

(OS) (Liu, 2000) methods with a different and

valuable view of the social context, and a WO

described in Web Ontology Language (OWL) that is

an interoperable SW Standard. As semantic refers to

meanings, and meanings are socially created by

humans, we expect to create a more faithful

computer ontology considering an information

system with a more abstract conceptual model that

can capture the behaviour of the involved agents.

In order to use the outcome of SAM (i.e. the OC)

with languages that describe WOs, it is necessary to

create a procedure that makes possible and explicit

the construction of OWL models from OC. The

objective of this paper is to propose heuristics to

perform this construction. The relations between the

models are mapped, and one model supports the

construction of the other. The paper is organized as

follows: Section 2 presents the Theoretical and

Methodogical Background; Section 3 describes the

heuristics proposed to create WOs aided by SAM;

Section 3 concludes and points out future works.

203

Cesar dos Reis J., Bonacin R. and Cecilia Calani Baranauskas M..

CONSTRUCTING WEB ONTOLOGIES INFORMED BY SEMANTIC ANALYSIS METHOD.

DOI: 10.5220/0003459602030206

In Proceedings of the 13th International Conference on Enterprise Information Systems (ICEIS-2011), pages 203-206

ISBN: 978-989-8425-56-0

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

2 THEORETICAL AND

METHODOLOGICAL

BACKGROUND

This section firstly presents an overview of the main

concepts of SAM; then some characteristics and

properties of WOs are presented.

2.1 Semantic Analysis Method

In SAM “The World” is socially constructed by the

actions of agents, on the basis of what is offered by

the physical world itself. The SAM assists users or

problem-owners in eliciting and representing their

meanings in a formal and precise model. In SAM,

the analyst in the role of facilitator specifies the

required system functions in an OC - a graphic

representation of a conceptual model. The OC maps

the vocabulary and the temporal relationships

between the percepts that those words represent and

describes a view of responsible agents in the focal

domain and their pattern of behaviour named

affordances (Liu, 2000).

Affordance, the concept introduced by Gibson

(1977) can be used to express the invariant

repertories of behaviour of an organism made

available by some combined structure of the

organism and its environment. In SAM, the concept

introduced by Gibson was extended by Stamper

(1993) to include invariants of behaviour in the

social world; affordances are social constructs in a

certain social context (Liu, 2000).

Agent is a special kind of affordance, which can

be defined as something that has responsible

behaviour. Agents are affordances that can take

responsibility both for their own actions and the

actions of others. An agent can be an individual

person, a cultural group, a language community, a

society, etc.

Ontological dependency is formed when an

affordance is only possible if certain other

affordances are available. We say that the affordance

“A” is ontological dependent on the affordance “B”

to mean that “A” exists only when “B” does; e.g.:

for a person to be able to stumble, he/she must first

walk; thus there exist an ontological dependency

between to stumble and to walk.

Determiners are properties which are variants of

quality and quantity that differentiate one instance

from another. Determiner are attributes that enable

one to describe an agent or an affordance;

Specialization, agents and affordances can be

placed in generic-specific structures depending on

whether they possess shared or different properties;

Whole-part, an agent or affordance can be part

of other agent or affordance. The part also owns all

the ontological dependencies from the whole;

Role-Name, an agent can have a specific role

depending on the affordance it has.

2.2 Web Ontology

The term ontology in Computer Science is often

used to refer to the semantic understanding (a

conceptual framework of knowledge) shared by

individuals participating in a given knowledge

domain. An ontology is used to formally specify the

concepts and relationships that characterize a certain

body of knowledge (domain). The formal nature of

ontologies makes them amenable to machine-

readability and provides a well-defined semantics

for the defined terms (Kalyanpur et al., 2004).

Figure 1: Ontology Chart for project management (adapted from Liu, 2000:79).

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A WO is usually described by computational

languages based on logic for knowledge

representation and inference. According to the SW

architecture proposed by Berners-Lee et al. (2001),

the ontology description languages are related to

other Web languages such as Extensible Markup

Language (XML), Resource Description Framework

(RDF) and RDF Schema (RDFS). In order to

address interoperability problems and to define a

universal paradigm for web-based exchange of

ontological information, the World Wide Web

Consortium (W3C) created the OWL which became

a W3C Recommendation (W3C, 2004). Using OWL

as a common language, knowledge experts and

application developers can create, modify, link and

import ontologies in a distributed environment.

OWL is an important piece of the future vision of

the Web, the SW.

3 HEURISTICS TO BUILD OWL

ONTOLOGY INFORMED BY

SAM

The first step of our approach is the application of

SAM in the context under study. An OC is created to

be the source model for the transformation to OWL

code. In order to accomplish that, a set of specific

heuristics must be followed to derive an initial OWL

ontology. The proposed heuristics are based on the

basic principles proposed by Liu (2000) and also by

Bonacin et al. (2004). They have proposed a set of

heuristics to construct Unified Model Language

(UML) diagrams from OC; those heuristics were

adapted to our purpose since there are conceptual

and practical differences between UML and OWL.

The OWL differs from UML in their proposals and

some key concepts such as methods and

composition. It is important to mention that by

applying the proposed heuristics does not guarantee

an equivalent ontology in OWL, and even the

transposition of all its properties; instead, it

represents some support to the analyst during the

modeling process. We assume that the analyst

should be in charge of evaluating the results and

determining the priorities (e.g. fidelity, maintenance,

reuse, and so on) over the modelling processes.

The proposed heuristics were classified

following the concepts from SAM such as:

affordances, agents, determiners, role-name, whole-

part, specialization and ontological dependence.

Figure 1 shows an example of an OC used to

didactically exemplify the approach with the

proposed heuristics. The heuristics with examples

from the OC of Figure 1 are presented as follows:

Affordances – During the SAM the world is

mainly modelled by the identification of social

constructions (affordances), while in the OWL the

world is modelled by the identification of classes

and individuals in the world. The presence of an

affordance in the OC suggests a class to be modelled

into the OWL ontology. For instance, considering

Figure 1, by the SAM perspective, a “project” is an

affordance of the society, and by the perspective of

WOs it can be a class with attributes. If the

affordance named “project” was represented in the

OC, this suggests that there is a class in the context,

and probably it is possible to refer to it using the

“project” name. Based on the procedure of

extracting names of classes from nouns, affordances

that are nouns can be mapped to classes in OWL

(i.e. affordances that suggest entities will be classes

in OWL). However, not all affordances are nouns,

for example the affordance “employ” which is a

verb. The affordances named as verbs will be

mapped to object properties in OWL. Thereby the

affordance “employ” will not be a class in OWL, but

it will be an object property named “employ”.

Agents – The heuristic suggest that all the agents

represented in the OC can be mapped as classes in

OWL and as sub-classes of a class called “Agent”.

This is carried out to identify the agents into the

OWL ontology, so all agents from the OC would

inherit the possible characteristics and properties

from the class “Agent”. Thus, agents such as

“person”, “organization”, “department” presented in

Figure 1 will be classes into the OWL ontology.

Determiners – The closest OWL concept to a

determiner is data property, which should be

connected to the appropriated class. As in the

example of Figure 1, the “function” determiner will

be a data property in OWL and its domain will be set

with the class “employee”; while the “dep_budget”

determiner will be mapped to the agent

“department”, then this data property domain will be

the “department” class.

Role-Name – In OC the role-name is always

connected to an agent. Hence from OC to OWL

role-names will be mapped as sub-classes of the

OWL classes that represent the agent in the left side

of the role-name. For instance, considering Figure 1,

the role-name “employee” will be mapped to a class

in OWL, and this class will be a sub-class of the

class named “person”; the same applies to the role-

name “employer”. The relation between the role-

name with the affordance in its right side can be

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better visualized in the transformation rule that may

implements this heuristic.

Whole-Part – There are two situations of whole-

part relation. First: when both the source affordance

and the target affordance are nouns, the affordances

or agents are mapped to classes; then an object

property called “partOf” can be created, and the

target class will be a restriction of this source class.

For example, in Figure 1, the class agent

“department”, mapped as a class in OWL will be

part of the agent “organization”, also mapped as a

class into OWL. In the second situation, both

affordances are verbs, so based on the affordance

heuristic described, both will be object properties in

OWL. Therefore, the target affordance will be

mapped to sub-property of the source affordance,

which is also an object property. Moreover, since

there is not part without the whole, when there is a

whole-part relationship there is also an ontological

dependence between the affordance of the whole and

the part.

Specialization – The specialization can be used

in agents, affordances or role-names; the

specialization relation between the generic and the

more specific type can happen between nouns and

also between verbs, as in whole-part relation. When

the more generic affordance type is an action and it

is mapped to an object property, then the more

specific affordance will be mapped to sub-property

of the object property in the OWL that represents the

more generic affordance. Nevertheless, when the

more generic affordance type is an entity (i.e. an

OWL class), and consequently is mapped to a class

in OWL, the more specific affordances will be

mapped to classes in OWL and they will be sub-

classes of the more generic class. The situation when

the more specific affordances are verbs is an

exception in the OC.

Ontological Dependence – This relation

between affordances is the most common in the OC

modeling. When an object cannot exist without

other, an association between classes can be

modelled into OWL. For example, the ontological

dependence that exists between the affordances

“society” and “person” in Figure 1 suggests an

association between then in OWL. For that, creating

an object property named “depends_on”, the source

affordance can be mapped to the range of this

property, and the target affordance is mapped to

domain of this property. Considering Figure 1, the

affordance “project” is ontologically dependent on

the affordance “organization”; thus the

transformation will create an object property stating

that “project” depends on “organization”. There is a

temporal relation between the ontological

dependence of two affordances; so an affordance

that depends on other will just exist while the other

exists. Nevertheless, just using the object property as

proposed in this heuristic is not enough to fully

represent the concept of ontological dependence of

SAM into OWL. Rules described in Semantic Web

Rule Language may be used to represent it.

4 CONCLUSIONS

The SW evolution depends on methods and

solutions that can adequately represent the

knowledge presented in Web applications content.

Heuristics to support the creation of a WO described

in OWL from the outcomes of the SAM were

presented with this proposal. The solution brings

opportunities to improve the semantic models used

in the existing SW applications. Next steps are the

construction of tools to implement the proposed

heuristics as transformation rules and the conduction

of practical experiments illustrating the application

of this approach.

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