Ontology Development to Handle Semantic Relationship between Moodle E-learning and Question Bank System

Yunianta, Arda; Yusof, Norazah; Jayadianti, Herlina; Othman, Mohd Shahizan; Suhaimi, Shaffika Mohd

doi:10.1007/978-3-319-07692-8_65

Cited by 3 publications

(3 citation statements)

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“…Data heterogeneity on applications aspect is about different data representation and types of information or data in different and numerous applications to support a learning process in education institutions [7]. Different applications are develop for specific purposes based on function and feature that included on that applications [5].…”

Section: Heterogeneity On Applicationsmentioning

confidence: 99%

“…Development of applications and information systems makes heterogeneity problems grow up and more complex, and from that problems need to find the best solution [3], [4]. Data on learning environment is increasingly grown up and becoming more meaningful to support learning activities [5], [6].Heterogeneity of data on learning environment is about different data representation and types of information or data in different and numerous applications to support a learning process in education institutions [7]. Different applications are develop for specific purposes based on function and feature that included on that applications [5].…”

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confidence: 99%

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Analysis and Identification the Complexity of Data Heterogeneity on Learning Environment Using Ontology

et al. 2015

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Distributed and various systems on learning environment are the current issues to produce big data and heterogeneity data problem. Heterogeneity on learning environment is about numerous learning applications and various learning information to support a learning process in educational institutions IntroductionImplementation of Electronic system on learning environments is becoming popular and very important in today's scenario because of their flexibility, convenience and accessibility to support learning activities in traditional learning process [1], [2]. There is numerous and various application systems on learning environment from different function and with specific purpose, this is usually known as heterogeneity on learning environment. The heterogeneity may be the difference in: User interface, Platform, Application system, Database system, Data representation etc.The heterogeneity of data is a current issue in distributed and various information sources. Development of applications and information systems makes heterogeneity problems grow up and more complex, and from that problems need to find the best solution [3], [4]. Data on learning environment is increasingly grown up and becoming more meaningful to support learning activities [5], [6].Heterogeneity of data on learning environment is about different data representation and types of information or data in different and numerous applications to support a learning process in education institutions [7]. Different applications are develop for specific purposes based on function and feature that included on that applications [5]. A lot of applications developed on learning environment, such as Teaching and learning online application, Library application system, Question bank system, Student management and payment system, Academic information management system, Student registration system and subject course evaluation system. In this paper, researchers are using UTM (Universiti Teknologi Malaysia) as a case study to analyze the data heterogeneity problem on university environment. With numerous applications that develop with various system and database schema, produces a big data with heterogeneity problem on that environment.

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Section: Heterogeneity On Applicationsmentioning

confidence: 99%

mentioning

confidence: 99%

Analysis and Identification the Complexity of Data Heterogeneity on Learning Environment Using Ontology

et al. 2015

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“…Data heterogeneity on learning environment is about different data representation and types of information or data in different and numerous applications to support a learning process in education institutions [4]. Different applications are develop for specific purposes based on function and feature that included on that applications [1].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Identification of Data Heterogeneity on Learning Environment Using Ontology Knowledge

Yunianta

Yusof

Aziz

et al. 2014

EECSI

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Heterogeneity on learning environment is about different data and applications to support a learning process in education institutions. Distributed and various systems on learning environment is the current issues to produce big and heterogeneity data problem. A lot of relationships are formed between elements on learning environment. The element on learning environment consists of learning data, learning applications, data sources, learning concept, and data heterogeneity aspect on learning environment. These elements are interrelated and produce complex relationship between each other. A complex relationship problem between elements on learning environment makes a process of analysis and identification difficult to be done. Existing method to drawing this heterogeneity problem make confuse and misunderstanding readers. To solved this problem, researcher using ontology knowledge to describe and draw a semantic relationship that represent the complexity of data relationship on learning environment. The result of this analysis is to develop ontology knowledge to solve complexity relationship on learning environment, and also to help reader's better understanding the complex relationship between elements on learning environment.

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Metadata Integration Framework for Data Integration of Socio-Cultural Anthropology Digital Repositories: A Case Study of Princess Maha Chakri Sirindhorn Anthropology Centre

et al. 2022

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Data integration is one of the most challenging tasks for digital collections whose data are stored across various repositories. Data integration across digital repositories has several challenges. First, data heterogeneity in terms of data schema and data values usually occurs across diverse data sources. Second, heterogeneity in data representation and semantic issues are among the problems. The same data may appear in different repositories with varied data representations, i.e., metadata schema. Recent research has focused on matching several related metadata schemas. In this paper, a metadata integration framework is proposed to support digital repositories in socio-cultural anthropology at the Princess Maha Chakri Sirindhorn Anthropology Centre (SAC), Thailand. The proposed framework is defined based on the Metadata Lifecycle Model (MLM). It utilizes non-procedural schema mappings to express data relationships in diverse schemas. A case study of metadata integration over the SAC digital repositories was conducted to validate the framework. The SAC common metadata schema was designed to support data mapping across 13 digital repositories. The SAC “One Search” system was developed to exemplify the system implementation of the framework. Evaluation results showed that the proposed metadata integration framework can support domain experts in socio-cultural anthropology in unified searching across the repositories.

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Ontology Development to Handle Semantic Relationship between Moodle E-learning and Question Bank System

Cited by 3 publications

References 13 publications

Analysis and Identification the Complexity of Data Heterogeneity on Learning Environment Using Ontology

Analysis and Identification the Complexity of Data Heterogeneity on Learning Environment Using Ontology

Analysis and Identification of Data Heterogeneity on Learning Environment Using Ontology Knowledge

Metadata Integration Framework for Data Integration of Socio-Cultural Anthropology Digital Repositories: A Case Study of Princess Maha Chakri Sirindhorn Anthropology Centre

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