A Proposed Ontology-Based Sociocultural Context Model

Fatma-Zohra Rennane

1,2

and Abdelkrim Meziane

Department of Computer Science, University of Science and Technologies Houari Boumedien, Bab Ezzouar, Algiers,

Algeria

Multimedia and Information System Division, Research Centre on Scientiﬁc and Technical Information, Ben Aknoun,

Algiers, Algeria

Keywords:

Context Model, Ontology, Socio-Cultural Proﬁle, Handicraft Women.

Abstract:

The global business landscape, including the handicraft sector in the Maghreb region, has witnessed a signiﬁ-

cant transformation with the emergence of Information and Communication Technologies (ICT). To adapt to

this evolving landscape, many businesses have made the strategic shift to online operations, capitalizing on

the vast opportunities offered by ICT. By establishing a strong online presence through e-commerce platforms

and social media, handicraft businesses can expand their customer reach and tap into a broader market. How-

ever, the adoption of ICT remains a formidable challenge for handicraft women. This challenge stems from

multiple factors such as poverty, gender disparities, language barriers, and limited literacy. To address these

obstacles and provide personalized services with relevant information, a context ontology integrating socio-

cultural aspects is proposed. This ontology serves as a comprehensive framework, capturing the socio-cultural

nuances of the handicraft sector. By leveraging this ontology, tailored ICT solutions can be developed, taking

into account the socio-cultural challenges faced by these women. This approach allows for the provision of

personalized services that align with their speciﬁc requirements, fostering the effective adoption of ICTs and

empowering handicraft women in the Maghreb region to thrive in the digital age.

1 INTRODUCTION

The rapid changes in Information and Communica-

tion Technologies (ICTs) have profoundly impacted

the global landscape, reshaping how people live,

work, and communicate. ICTs have become indis-

pensable tools for running competitive businesses,

presenting new opportunities for handicraft women

to start and expand their ventures. Through various

forms of ICTs, both traditional and emerging, handi-

craft women are able to connect with customers, in-

crease efﬁciency, and grow their businesses in ways

that were previously inaccessible to them (UNCTAD,

2013) (Women, 2017).

However, the adoption of ICTs remains a signif-

icant challenge for handicraft women from emerging

countries. This challenge can be attributed to a range

of factors, including poverty, gender inequality, lan-

guage barriers, limited literacy levels, and sociocul-

tural factors. These barriers impede women’s access

to and effective use of ICT tools and resources, limit-

ing their ability to fully harness the beneﬁts of digital

technologies(UNCTAD, 2013).

Simultaneously, technological advancements have

revolutionized the way users interact with digital sys-

tems and devices. Traditional computing approaches

have focused on processing data and providing static

solutions. However, the emergence of context-

aware computing has brought about a paradigm shift.

Context-aware computing enables systems to dynam-

ically adapt and respond to users’ contextual infor-

mation, creating personalized and adaptive function-

alities.

The fundamental concept behind context-aware

computing is recognizing that users’ needs and pref-

erences can vary depending on the speciﬁc context in

which they are interacting with a system. By integrat-

ing contextual information, systems can offer tailored

experiences, improving intuitiveness, efﬁciency, and

responsiveness to users’ requirements.

In this context, context-aware computing holds the

potential to address some of the challenges faced by

handicraft women in adopting ICTs. By considering

the speciﬁc contextual factors that inﬂuence women’s

engagement with ICTs, such as their sociocultural

background, language preferences, and literacy lev-

els, context-aware systems can provide more inclu-

sive and customized solutions. This can help bridge

Rennane, F. and Meziane, A.

A Proposed Ontology-Based Sociocultural Context Model.

DOI: 10.5220/0012173200003584

In Proceedings of the 19th International Conference on Web Information Systems and Technologies (WEBIST 2023), pages 215-222

ISBN: 978-989-758-672-9; ISSN: 2184-3252

215

the digital divide and empower handicraft women in

emerging countries to effectively leverage ICTs for

their entrepreneurial pursuits.

This research is founded on a project that investi-

gates how women engaged in handicrafts in develop-

ing or emerging regions employ modern technologies

to foster both their creativity and business initiatives.

The objective of this research is to introduce a per-

sonalized framework based on ontology, facilitating

both training and organizational solutions tailored for

handicraft women. This approach takes into account

the incorporation of social and cultural aspects within

the context model, which constitutes the primary fo-

cus of this paper.

The subsequent sections of this paper are struc-

tured as follows. Section 2 presents a review of exist-

ing research and studies that have explored ontology-

based context models. Section 3 outlines the ontology

development process employed in this study. Section

4 describes the elements proposed in the ontology.

Section 5 concentrates on the validation phase. Fi-

nally, section 6 summarizes the conclusions and sug-

gests directions for future research.

2 RELATED WORK

In the past few years, numerous research endeavors

have been dedicated to the development of context

ontologies. However, there is currently no universally

accepted model that can be readily applied for context

knowledge representation across various applications.

Among the early works, the CoDAMos ontology

(Aguilar et al., 2018) emerges, encompassing four

primary entities: user, environment, platform, and

service. Another notable example is the CONON

(CONtext ONtology) (Wang et al., 2004), which em-

ploys logical reasoning to deduce implicit and explicit

context within pervasive computing environments. It

incorporates fundamental concepts like person, activ-

ity, computational entity, and location, which can be

extended by incorporating domain-speciﬁc concepts.

The SOUPA ontology (Chen et al., 2004) serves to

model context for pervasive computing environments,

comprising the SOUPA Core, which deﬁnes general

terms applicable to different pervasive computing ap-

plications, and the SOUPA extensions, which intro-

duce additional concepts to support speciﬁc applica-

tion types.

CAMeOnto (Aguilar et al., 2018) is an ontology

that captures generic concepts at a higher level by fa-

cilitating the hierarchical extension of speciﬁc con-

textual information. It is utilized by the context-aware

reﬂective middleware called CARMiCLOC and is de-

signed based on the 5W principles: who, when, what,

where, and why. Additionally, the CAMeOnto con-

sists of six contextual classes: user, activity, time, de-

vice, services, and location.

(Yin et al., 2015) introduced an alternative study

that suggests a hierarchical model for context, fo-

cusing on the features of work-based learning. This

model includes a shared layer with a common ontol-

ogy and a domain-speciﬁc layer containing a general-

ized ontology for work-based learning and a speciﬁc

ontology for work-related contexts.

Another approach presented in (Ouissem et al.,

2021) is a generic context model based on ontology

for ubiquitous learning. The model provides a frame-

work for representing and managing context informa-

tion in a way that supports adaptive and personalized

learning experiences in ubiquitous learning environ-

ments.

In (Cabrera et al., 2019), the 3LConOnt represents

a three-level model comprising an upper-level ontol-

ogy representing the highest abstract level, a middle-

level ontology consisting of reusable modules adapt-

able within the same level, and with the upper and

lower-level ontologies, and a lower-level ontology

that characterizes domain-speciﬁc classes and prop-

erties.

While these research works primarily focus on

modeling context of a physical nature, such as loca-

tion, time, and activity, there have been limited ef-

forts in investigating socio-cultural contexts, includ-

ing educational level and emancipation level. Some

endeavors (Chen and Kotz, 2000), (Dey, 2001) have

attempted to adopt and extend the Friend of a Friend

(FOAF) (Perera et al., 2013) ontology to represent so-

cial relationships. Other works (Kabir et al., 2014)

have established effective social information manage-

ment platforms and proposed the SCOnto ontology,

which deﬁnes general concepts like social role, social

relationship, social interaction, and social situation,

and extends these concepts to incorporate domain-

speciﬁc elements.

3 THE ONTOLOGY

DEVELOPMENT PROCESS

The process undertaken in this paper to build the on-

tology involved two main stages: the knowledge ac-

quisition stage, and the ontology construction stage.

3.1 Knowledge Acquisition

In the knowledge acquisition stage, the essential in-

formation for constructing the ontology was obtained

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216

Figure 1: The Upper Ontology.

from a variety of credible sources, including domain

experts’ opinions such as sociologists and association

members, recent literature and guidelines, as well as

interviews conducted with 77 handicraft women of di-

verse backgrounds coming from both rural and urban

areas. These interviews mainly center around socio-

demographic data, craft production nature, produc-

tion process, coordination and communication tools

used, and implicit needs.

3.2 Ontology Construction

In the realm of ontology design, various research

groups have endeavored to facilitate the process of

ontology engineering leading to the proposal of dif-

ferent methodologies (Fern

andez-L

opez et al., 1997;

De Nicola et al., 2009; Staab et al., 2001), all consid-

ering essentially the following steps:

3.2.1 Speciﬁcation Phase

This phase states the scope and the purpose of build-

ing the ontology. The main objective of the proposed

ontology is to introduce context-awareness concepts

that can effectively address pervasive environments.

These pervasive environments encompass various pa-

rameters such as location, service, environment, and

others, as depicted in the upper ontology illustrated in

Figure 1. Moreover, the ontology aims to integrate the

socio-cultural characteristics that are crucial in shap-

ing individual behaviors within this context.

3.2.2 Conceptualization

This step identiﬁes and deﬁnes the key concepts and

entities within the domain. Determine the relation-

ships between these concepts, such as hierarchies, as-

sociations, attributes, and dependencies by establish-

ing a structured representation of the domain knowl-

edge. An excerpt of the concept glossary is depicted

in Table 1.

3.2.3 Formalization

This phase transforms the outcome of the previous

action into a formalized model using a suitable on-

tology language. In the present study, the OWL lan-

guage (Web Ontology Language) is employed for this

purpose. OWL is a widely used ontology language

that provides expressive capabilities for representing

Table 1: Excerpt of the concept glossary.

Concept Description

ContextElement The main concept repre-

senting the entry point to

the model

User end-user, participant, per-

former, etc.

TechnicalEntity Technical concepts such

as device, bandwidth, etc.

Environment Presentes the surrounding

environment that can be

physical (weather, temper-

ature, etc.) or socioProfes-

sional

SocioProfessional

Environment

presentes socioprofes-

sional relationships

SocioCulturalProﬁle User’s sociocultural pro-

ﬁle

GossipImpact Numerical value indicat-

ing the degree of inﬂuence

that gossip has on individ-

uals

EmancipationLevel Numerical value indicat-

ing the degree of liber-

ation from sociocultural

constraints

Languages Natural languages used by

the user

Religion User’s religion (Muslim,

Christian, etc.)

ICTUsage Modality of ICT used by

the user

Location Indicates the user’s posi-

tion

MaritalSituation Can take the values:

married, single, divorced,

widow

knowledge and deﬁning relationships between enti-

ties in a structured manner.

3.2.4 Implementation

The implementation phase of ontology development

requires the use of a suitable tool that facilitates on-

tology modeling, editing, visualization, and reason-

ing. In this paper, the Prot

framework is used.

Prot

e provides a comprehensive set of features and

functionalities that aid in the development and man-

agement of ontologies. It offers a user-friendly inter-

face, support for various ontology languages, integra-

tion with reasoners, and visualization tools, making

it an ideal choice for implementing ontologies in this

https://protege.stanford.edu/

A Proposed Ontology-Based Sociocultural Context Model

217

Figure 2: The Socio-cultural Proﬁle Ontology.

research.

3.2.5 Validation

Validate the ontology is the step to ensure its correct-

ness, completeness, and adherence to the intended de-

sign. Conduct tests and evaluate the ontology against

predeﬁned criteria to identify any inconsistencies,

ambiguities, or errors that need to be addressed.

4 ONTOLOGY DESCRIPTION

4.1 The Upper Ontology

The generic ontology illustrated in Figure 1 is an

upper-level ontology that captures the fundamental

contextual entities found universally in all pervasive

environments. Context can be classiﬁed into ﬁve main

categories namely User (user proﬁle, socio-cultural

background, skills), Environment (physical, compu-

tational), Process (activity, business process, learn-

ing process), service (computing services, social ser-

vices), and TechnicalEnity (Device, Software, etc.).

4.2 User Ontology

This ontology refers to an individual who interacts

with a system, application, or environment. It rep-

resents the entity that utilizes and engages with the

functionalities, services, and resources provided by

the system. In this ontology, the user concept captures

various attributes and characteristics of the user that

are relevant to the system or application being con-

sidered. It covers the personal proﬁle, socio-cultural

proﬁle, and socio-professional proﬁle.

• Personal proﬁle: speciﬁes the personal informa-

tion about a user, demographic information, hob-

bies, preferences, handicaps, disabilities, and per-

sonality traits.

• User proﬁle: describes the information needed to

use the system such as login and password, etc.

• Learner proﬁle: covers the information related to

a learner such as learning aims, learner’s level,

learning preferences, etc.

• Socio-cultural proﬁle: describes the user’s cul-

tural background such as emancipation level, gos-

sip impact, etc.

• Business proﬁle: consists of the user’s job infor-

mation, skills, diplomas, etc.

Figure 2 and Figure 3 present an excerpt of the so-

ciocultural proﬁle ontology and business proﬁle on-

tology respectively.

4.3 Environment Ontology

The environment constantly provides information that

enables users to make suitable decisions or has the

potential to impact their behaviors. In the proposed

model, the environment ontology is composed of two

main components:

• The physical environment: which describes the

physical conditions and the ambient parameters

such as weather, temperature, location, time, etc.

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Figure 3: The Business Proﬁle Ontology.

Figure 4: The Socio-professional Environment Ontology.

• The socio-professional environment: illustrated in

Figure 4, shows the different socio-professional

relationships between users and their role in var-

ious existing communities such as professional

communities, and social communities.

4.4 Technical Ontology

The technical ontology shown in Figure 5 describes

information about the device used, equipment, sen-

sors, software, and computational parameters.

4.5 Process Ontology

The process ontology provides a description of the

main elements of a process. A process is composed

of some activities which are decomposed into tasks.

A transition describes the passage from one activity

to another under certain conditions. The Resources

concept describes tools and materials used to accom-

plish a speciﬁc task. The business process ontology

describes the main steps to complete a speciﬁc work

in the handicraft domain such as making carpet, mak-

ing pastry, and making pottery. Figure 6 present an

excerpt of the business ontology.

4.6 Service Ontology

The service ontology models information about com-

putational services and socio-professional related ser-

vices.

• A computational service is a functionality that can

be consumed by users, applications, or other ser-

vices In this work we adopt the OWL-S (Mar-

tin et al., 2004) ontology which gives informa-

tion about service providers with a set of classes

describing services’ characteristics by specifying

the service functionalities (service model), ser-

vice description (service proﬁle), and access de-

tails (service grounding), for example: order ser-

vice, delivery service, and e-payment service. The

Figure 7 shows an excerpt of this ontology.

• A socio-professional services presented in Figure

8, specify human-related services that help the

users manage a a speciﬁc part of their business,

for example, the ﬁnancial helps provided by the

government or associations, the training services

offered to help the handicraft woman learn new

methods or to use new tools.

5 VALIDATION

The validation step in the ontology development pro-

cess is a crucial stage that aims to ensure the quality,

correctness, and reliability of the ontology. It involves

conducting various tests and assessments to evaluate

the ontology against predeﬁned criteria and require-

ments. In this paper, two main strategies are applied:

consistency checking, and rule-based reasoning.

5.1 Consistency Checking

This strategy involves conducting consistency check-

ing, which veriﬁes the logical coherence of the ontol-

ogy by examining the deﬁned relationships and ax-

ioms. Its purpose is to ensure that there are no con-

tradictory or inconsistent elements in the ontology’s

logical structure. To accomplish this, the Pellet rea-

soner is used (Sirin et al., 2007). Figure 9 shows that

the ontology did not produce any misinterpretations

when the reasoner was active. In this ﬁgure, the whole

ontology consists of 2071 Axioms, 186 classes, 134

object properties, 36 data properties, and 507 individ-

uals.

A Proposed Ontology-Based Sociocultural Context Model

219

Figure 5: The Technical Concept Ontology.

Figure 6: The Process Ontology.

Figure 7: The Computational Service Ontology.

Figure 8: The Socio-professional Service Ontology.

5.2 Rule-Based Reasoning

Rule-based reasoning is a form of logical inference or

deduction that uses a set of predeﬁned rules to draw

conclusions from given facts or assertions. It involves

applying logical rules or condition-action pairs to de-

rive new knowledge or make logical deductions based

on the available information. Semantic web Rule

Figure 9: Consistency checking and ontology metrics.

Language is an important formalism for expressing

knowledge in the form of rules. SWRL is used to de-

ﬁne inference rules in knowledge models represented

in OWL in a semantically consistent way (Ye et al.,

2015). In this work, the ontology model has been en-

riched with a set of rules illustrated in Figure 10.

These rules are used to respond to some compe-

tency questions such as: to which socio-cultural pat-

tern does a handicraft woman with speciﬁc charac-

teristics belong? What is the socio-professional situ-

ation of a handicraft woman? The answers to these

questions are illustrated in Figures 11, 12, and 13.

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Figure 10: Excerpt of the rules used in the model.

Figure 11: First Example of the inference related to the ﬁrst question.

Figure 12: Second Example of the inference related to the ﬁrst question.

Figure 13: Example of the inference related to the second question.

A Proposed Ontology-Based Sociocultural Context Model

221

6 CONCLUSIONS

This paper introduces a context model based on on-

tologies, which includes an upper ontology deﬁning

fundamental context concepts, as well as several on-

tologies that describe speciﬁc aspects of the context

such as environment, service, and user. It highlights

the signiﬁcance of incorporating the socio-cultural

and socio-professional attributes of users into the con-

text model.

This contribution is still in progress. In future

works, the intention is to utilize the context ontology

and demonstrate its applicability in a real-world ap-

plication, showcasing its adaptability based on cap-

tured context. Additionally, an important objective is

to assist handicraft women in the Maghreb region by

enabling them to adopt and adapt ICT technologies

to meet their speciﬁc service requirements within di-

verse contextual scenarios.

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