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

Arda Yunianta (Faculty of Computing, University Teknologi Malaysia)
Norazah Yusof (Faculty of Computing and Information Technology, King Abdul aziz University, Rabigh)
Abdul Aziz (Faculty of Information Technology and Communication, Mulawarman University)
Nataniel Dengen (Faculty of Information Technology and Communication, Mulawarman University)
Mohd Shahizan Othman (Faculty of Computing, University Teknologi Malaysia)

Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 1: EECSI 2014

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.