Semantic data mapping on e-learning usage index tool to handle heterogeneity of data representation

Abstract

Distribution and heterogeneity of data is the current issues in data level implementation. Different data representation between applications makes the integration problem increasingly complex. Stored data between applications sometimes have similar meaning, but because of the differences in data representation, the application cannot be integrated with the other applications. Many researchers found that the semantic technology is the best way to resolve the current data integration issues. Semantic technology can handle heterogeneity of data; data with different representations and sources. With semantic technology data mapping can also be done from different database and different data format that have the same meaning data. This paper focuses on the semantic data mapping using semantic ontology approach. In the first level of process, semantic data mapping engine will produce data mapping language with turtle (.ttl) file format that can be used for Local Java Application using Jena Library and Triple Store. In the second level process, D2R Server that can be access from outside environment is provided using HTTP Protocol to access using SPARQL Clients, Linked Data Clients (RDF Formats) and HTML Browser. Future work to will continue on this topic, focusing on E-Learning Usage Index Tool (IPEL) application that is able to integrate with others system applications like Moodle E-Learning Systems.