Paper Title (Use Style: Paper Title) s38

International Journal of Enhanced Research Publications, ISSN: XXXX-XXXX Vol. 2 Issue 4, April-2013, pp: (1-4), Available online at: www.erpublications.com

A Socio-Cultural Context Ontology Application to Handicraft Women from the Maghreb Regions

Valérie Monfort1, Farah Bellaaj1, Mourad Abed1 1 University of Valenciennes, LAMIH, CNRS UMR 8201, Valenciennes France [email protected], [email protected], [email protected]

Abstract: The notion of context is extensively investigated in mobile and pervasive application to define locative and temporal aspects in dynamic applications. Context is generally defined as "any information that can be used to characterize the situation of an entity". However, we believe mobile applications are not only device-centric, platform specific and infrastructure dependent, they also find out about user's personal information as socio-economical context. So, the principal strength of our approach is the integration of context-aware pervasive systems, actors' profiles, actor's skills and semantics. Instead of proposing new context ontology, we extend current proposals with profile and skills, to offer personalized services with suitable information. We firstly validate the proposed extended context ontology and then, we use this ontology in a concrete application based on the usage of Information and Communication Technologies (ICT) by Handicraft Woman in Maghreb regions.

Keywords: context, ICT, ontology, pattern, socio-cultural profile, skill.

Introduction

The emergence of new technologies in particular wireless communications and the increasing use of portable devices (smart phones, personal digital assistants (PDA), laptops…) have simulated the emergence of a new computing paradigm called: pervasive computing. Pervasive computing firstly introduced in 1991 by [18], refers to the seamless integration of devices into the users everyday life. “Appliances should disappear into the background to make the user and his tasks the central focus rather than computing devices and technical issues”. Moreover, context is defined as any information that can be used to characterize the situation of an entity such as: location, identity (user), activity (state) and time [3] [19]. The definition proposed in [4] also presents the context as being hierarchically organized and differentiates between environmental information which determines the behavior of mobile applications and which is relevant to the application. It is difficult to give a complete definition for a context and, in fact, the notion of context is not universal but relative to some situation and application domain. Basically, context should answer the following questions: “who?”, “what?”, “when?” and “where?” and, ideally, should allow the system to answer one last question: “why?”. The Semantic Web provides the foundation for semantic architecture to support the transparent exchange of information and knowledge. Recent advances in the Semantic Web technologies offer means for organizations to exchange knowledge in a meaningful way. Previous research works allowed us offering a context model based on current works on pervasive computing [30]. We believe mobile applications are not only device-centric, platform specific and infrastructure dependent, they also find out about user’s personal information. We also believe users are human beings with personal socio-cultural information, as their profile, their skills, etc, as found for instance in SIOC [16] with social networks and in M or E- learning. We can define socio-cultural profile as information characterizing any population segment which can be identified by its different communities, habits, behaviors, trends, etc. Improving knowledge on socio-cultural profile of a population allows a better understanding of the manner to fit to its expectations. So, in our opinion, personal socio-cultural information can be considered as context concepts which impact on Human Man Interface, functionalities to deploy, decision, strategy to choose, etc. However, we do not aim to propose a new context model because too many research works have done it before without any consensus. We aim to extend these research works with socio-cultural profile and skills, to propose personalized services with suitable information to characterize an

Page | 1 actor (user, member of a social community, learner, etc). We also propose a set of patterns, where ontology design pattern (ODP)is a reusable successful solution to a recurrent modeling problem [31]. Our research work is based on a research project studying the manner handicraft women of third world or emergent countries use new technologies such as: Internet and social networks with devices as phone, smart phone, laptop, tablet, etc, to develop their creativity and their business activity. We noticed several problems such as: 1) Socio- economic constraints as illiteracy, poverty, etc, 2) Few means to learn and to develop business activity with ICT (Information and Communication Technologies), 3) Sociologic and cultural diversities according to location. Based on extended context-ontology, the second originality of our research work includes following three improvements: 1) To define a tool to detect what are socio-cultural lags and handicraft women’s expectations, 2) To propose and to analyze roles play by studying indicators as in [29], 3) To propose technical, organizational and training solutions with pattern reuse. This paper is structured as followed. Section 2 describes related works and aims to justify proposed model. Section 3 presents context ontology and patterns. Section 4 proposes the implementation of the context ontology and patterns usage. Section 5 concludes our paper and presents some suggestions for future works.

Related works

Currently, different approaches have been used for building context ontologies and broadly described in [14]. However, there is no widely accepted model that can be reused for modeling context knowledge in different applications. The ASC (for Aspect-Scale-Context) model [23] includes as core concepts the following ones: aspects, scales, and context information. Authors in [24] propose a W3C initiative which shows an infrastructure to describe device capabilities and user preferences. The representation model consists of a hierarchical structure of components divided into the following three areas: hardware, software and application. COBRA-ONT [25] is an ontology that defines some of the common relationships and attributes that are related to people, places and activities. COBRA- ONT defines key ontology categories such as action, agent, time, space, device, etc. The CoDAMoS [26] ontology defines four main core entities: user, environment, platform, and service. CONON [27] (for Context Ontology) defines general concepts such as location, activity, person or computational entity, whose terms are thought to be extensible in a hierarchical way by adding domain specific concepts. SOUPA [2] is divided into two main blocks called SOUPA-Core and SOUPA-Extensions. SOUPA-Core defines concepts that should appear in a lot of scenarios (e.g., person, agent, policy, time, space), while SOUPA-Extensions supports particular concepts in narrower domains (e.g., home, office, entertainment, etc). As mentioned in introduction, these research works focus on: environment, device, interface, network, provider, role, service, source, time, etc) but mobile applications are not only device-centric, platform specific and infrastructure dependent. We believe socio-economic information is of major importance for context model definition. Many mobile applications also find out about user’s personal information. Moreover, some ontologies (CC/PP, COBRA- ONT, CoDAMoS, etc) generally propose simple and limited information about the user (name, surname, login, password, address, email, etc). But, these models do not offer solution if user, for instance, does not speak English, or he cannot read because he is disabled or illiterate. Application has to take into account this constraint by proposing suitable services at run time. Sociologists as [28] maintain context typically consists of at least the following major categories, possibly each with their own internal schematic structure, as: setting (location, timing of communicative event), social circumstances (previous acts, social situation), institutional environment, overall goals of the (inter)action, participants and their social and speaking roles, current (situational) relations between participants, global (non-situational) relations between participants, group membership or categories of participants (e.g., gender, age). Moreover, social networks with SIOC and FOAF [17] simply record a set of terms that are useful to the Web community, while keeping an emphasis on the central idea of FOAF, which is about linking networks of information with networks of people. We can mention some information as: agent, person, name, title, image, depiction (depicts), family Name, given Name, a person known by this person, based near (a location that something is based near), age, made (maker) (an agent who made this), etc... M or E-learning proposes several learning context ontologies. Moreover, E-learning domain uses specific standards as IMS-LD (Instructional Management Systems-Learning Design) [21] and LIP (IMS Learner Information Package) [22] which offer advanced ontologies to characterize actors with profile, skills, learning contents including learning activities and processes, etc. For industrial applications, [15] has introduced an ontology-based skill management for large insurance company. Authors in [16] aim to facilitate the management of available human resources’ skills and competencies, international specifications for competency description and totally or partially automated techniques for construction of expert profiles. They underline the degree of importance the learner’s skill level and improvement for skill acquisition, the data concerning experiences of the skill, including the quality and the period of time involved with the skill, the data that explains the content of the skill, data concerning know-how of skill, the comprehensive utilization of media in skill expression [20]. Based on presented ontologies (FOAF, LD/LIP, human resources) and sociology thinking, we defined our own ontology.

Ontology Proposal

Page | 2 International Journal of Enhanced Research Publications, ISSN: XXXX-XXXX Vol. 2 Issue 4, April-2013, pp: (1-4), Available online at: www.erpublications.com

1.1. General Approach

There are various methodologies to design ontology [6] [7] [9] [10] [11]. All of them consider basically the following steps: definition of the ontology purpose, conceptualization, formalization, and validation. We defined our context ontology by using these steps. The conceptualization is the longest step and requires the definition of the ontology’s scope, definition of its concepts, relations and constraints, and a description of a glossary for all concepts and attributes specified. It represents the knowledge modeling itself. The formalization consists of expressing the ontology in some language and code in a specific tool. This ontology was formalized with WSML, using Protégé. Those steps will be presented in this section. Ontology validation remains an important open problem in the area of ontology-supported computing and the semantic web. Instead, the choice of a suitable approach must depend on the purpose of validation, the application in which the ontology is to be used, and on what aspect of the ontology we are trying to validate [1]. Finally we decided to validate our ontology by instantiating it with genuine instances examples based on the community of handicraft women from Maghreb regions.

1.2. Purpose

Based on these works we proposed an ontology integrating previous models showing following concepts: Context awareness to address pervasive environment with: context element including environment (parameters with location, time, weather, etc, socio-professional environment, services, technical concepts, actors). Socio-economical profile description, according to actor and his personal properties (name, surname, address, birthday date, etc) which includes profile and actor centric concept [13]. 1. Profile with disability, habits, hobby, preferences, and which includes skills. Profile can be refined with Socio cultural profile. Socio cultural profile which includes transportation means, job information, diploma, marital situation, temper, emancipation level, gossip impacts, religion, ICT usage, does the actor benefit human development program. 2. Skill concerning: domain, skill level, personal aims to achieve to improve skills, driving license, languages.

1.3. Conceptualization

1.3.1. Scope of the context ontology We start this step by defining the following competency questions, i.e., requirements in the form of questions that the ontology must answer: 1.3.1.1. To which socio-cultural category does a person belong? 1.3.1.2. What is the socio professional situation of an actor? What is the actor’s Curriculum vitae? 1.3.1.3. What is ICT usage per socio-cultural category and actor? 1.3.1.4. What are the impacts of socio cultural lags on ICT usage per socio-cultural category of person? 1.3.1.5. What are the services and government helps which are offered to an actor according to his profile and socio-cultural lags? 1.3.1.6. What are professional and ICT usages improvements for an actor?

1.3.2. Ontology description Firstly, we describe the context aware part of the ontology (Figure 1). The main concept of the context model is the Context Element. Several concepts inherit from Context Element such as: event, manager and interaction. These concepts aim to manage events and information coming from different devices and environment. Environment, Actor, technical concept, service, interaction event, inherit from Context Element. This environment includes parameters as location, time, weather, etc. Socio Professional Context inherits from the environment. It indicates the nature of socio professional links with others as Collaboration, Cooperation, crowd sourcing and different Communities (racial, familial, professional, and virtual). These communities can be racial, familial, professional, virtual, etc. Other concepts as Actor, services and technical concepts are Context Elements. The actor has one or several Profiles, and Actor Centric Concepts. Actor Centric Concepts are information from Actor via Interceptors. Technical Concepts are Device, Equipment and Interceptors. They are sold by distributor and designed by constructor. Services are described by their Service Level Agreement (SLA), their functional scope, their Quality of Service (QoS), their URL, and the cost if provider asks for payment to use service after invocation.

Page | 3 Secondly, we present the actor with profile and skill part which can be common to current ongoing research works (Figure 2). Actor includes actor centric concept and is detected by interceptor. The actor has a profile which includes skills, possible disability, habits, hobby, and preference (for instance the actor prefers pink color).

Part of the ontology related to Context Element.

Skills are composed of different concepts as skill on one or several domains, skill level, the personal aims of the actor he has or he wants to achieve with his aims, the targeted level, the process with the activities to master, the kind of driving license, the languages (read, written, spoken) mastered by the actor and to witch level.

Part of the ontology related to Actor and skill.

Socio-cultural profile is a kind of profile having different informational aggregates about Job, diploma, marital situation, temper, gossip impacts, religion, ICT usage, if actor benefits human development program, and if the actor

Page | 4 International Journal of Enhanced Research Publications, ISSN: XXXX-XXXX Vol. 2 Issue 4, April-2013, pp: (1-4), Available online at: www.erpublications.com owns one or several transportation means (Figure3). Information about job are the address, telephone, mail, the manager of the actor, the role of the actor, his function, the specificities of the job, the number of persons managed by the actor, the starting date of the employment contract, the possible ending date with reasons, income from this job, extra job (other activity), extra income coming from extra activity, creativity level, motivation, number of working hours per week. Emancipation level impacts or not on the professional activity (job). Diploma is characterized by a level, an organization (university), a domain, a degree, a date when he obtained the diploma, industrial or pedagogical placement (starting date of the placement, the domain, aim of the placement).The list of used ICT with the aim (calling client, buying by Internet, etc), the duration of the usage, the achievement of the aim.

1.3.3. Glossary All the concepts and attributes are clearly defined in a glossary (see Table I for the most relevant concepts). Theses definitions are based on sections 3 and are proposed by following link (Glossary).

Part of the ontology related to Socio Cultural Profile. (figure caption)

1.4. Formalization

The left side of Figure 4 represents an excerpt of implemented ontology where nodes are concepts and colored links are the relation between concepts. It was designed from previous figures. The ontology was formalized using OWL 1.0 and Protégé. The right side of Figure 4 shows the hierarchy defined in Protégé: classes, subclasses and sibling

Page | 5 classes. Figure 5 shows formalization in OWL of an extract of context with Profile and Skill. SocioCulturalProfile is defined as a subclass of Profile and which is aggregated into several other concepts such as Religion, MaritalSituation, Diploma, Job, etc via the suited ObjectProperty. The cardinality of the association between these concepts is formalized by the Max and Min cardinality in Protégé. In this paper, we propose some examples of patterns as Formal expressions in SWRL (Semantic Web Rule Language), we implemented in our system. Figure 6 shows Person_To_Help Pattern which selects the individuals depending on their language level skill, diploma level and job income and permit to classify them into four groups. The aim of this pattern is to get a list of persons which can be helped with training, organizational means, etc. Figure 7 shows ICT_Usage_Person Pattern which classifies ICT Usage of individuals depending on their profile, skills and ICT Aim. Figure 8 shows LAGS_ICT_USAGE_Person which categorizes lags that reduce the adoption of ICT Usage taking into account the impact of religion, gossip and emancipation level.

Ontology graph and Ontology hierarchy in Protégé.

OWL code for the part of extended context ontology

SWRL Expression: Person_To_Help Pattern.

SWRL Expression: ICT_Usage_Person Pattern.

Page | 7 SWRL Expression: LAG_ICT_USAGE_Person Pattern.

Application A. Usage Scenario

We also elaborate twelve other patterns which reuse generic patterns presented above but they are not all mentioned in this paper to meet size limitation. However, we present an example of the first one (Figure 6) which classifies the handicraft woman into four groups depending on their language skill, diploma and job income. We know with this pattern our study has to focus on the women of class B: women from inland region, with low income, with strong socio-cultural lags impacts, illiterate, etc. The execution of the rule detailed in this pattern selects person , especially handicraft woman with language level (read, spoken and written) less than 2, diploma level less than 2, diploma in sewing, job income is more than 51 and do not exceed 100 and classify them in the Class_B_Woman.

SWRL Expression: Class_B_Woman_Pattern.

By using Jess engine, all axioms and SWRL rules defined in our ontology are executed and the result is presented in Figure 10.

Number of axioms inferred using Jess engine.

Let us suppose that we have an actor named "Mongia" with the following characteristics: sex = female, read level = 1, spoken level = 1, written level = 1, diploma = sewing, diploma level = 1 and job income = 60. This actor will be inferred as member of the Class_B_Woman (Figures 11 and 12). Figure 13 shows a SPARQL request to get information about ICT usage according to women classification.

Actor1 inferred as member of Class_B_Woman_Pattern.

Mongia Details.

Gossip Level, Emancipation Level, Religious Constraints and ICT Usage.

Conclusion and future works

This research work aims to propose context ontology extended to socio-cultural profile and skill. The results presented in this paper involved a 120 handicraft women, in the future, we would like to extend the number of

Page | 9 women to 500 for better results. We also propose a more suitable solution with Web Data Mining. Web Mining rapidly collects and integrates information from multiple Web sites. We suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and Web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between handicraft women’s behavior, context, profile, skills, training and training strategy. If there are some training solutions, however, which are not retrieved by data mining, we can’t recommend additional information or retrieve distant training services. In this case, we can use CBR as a supplementary AI (Artificial Intelligence) tool to recommend the similar purchase case. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect association knowledge, socio cultural context and training strategy. We aim to go further in the tool development and to propose a training environment. We also would like to improve teaching processes adaptability with indicators to measure skills and to propose new teaching strategy. Further, authors described an implementation of an Adapter that converts XML to a Web Service Modeling Language (WSML). WSML is the language used to describe Web Service Modeling Ontology (WSMO) concepts, related to Semantic Web services (SWS). SWS are web services that are semantically annotated. The semantic annotation is necessary to address various business logics in an appropriate manner, thus allowing complex business applications to be built and executed. The Web Service Execution Environment (WSMX) is an execution environment for dynamic discovery, selection, mediation and invocation of semantic web services. WSMX is a reference implementation for WSMO.

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