Development of Ontology through Different Advances of Ontology Mapping SYERINA AZLIN MD NASIR & NOR LAILA MD NOOR Faculty of Computer Science and Mathematics Universiti Teknologi MARA 40000 Shah Alam MALAYSIA syerina@kelantan.uitm.edu.my, norlaila@tmsk.uitm.edu.my Abstract: - Existing ontology mapping tools differ in terms of the task for which the mapping tools are designed. As a result, direct comparison is difficult to conduct due to the disparate nature of the tools. In this paper, a benchmark case of manual mapping is used to compare the mapping results between selected mapping tools. The benchmark is set up which is based on the manual mapping between Revised Traditional Malay Textile (TMT) Knowledge Model and CIDOC CRM. For comparison, similar mappings are conducted using selected mapping tools based on the categories defined. Based on the finding, an evaluation framework on the quality of mapping is proposed which mainly focuses on three design criteria which are efficiency, effectiveness and efficacy. In future, this work will help to determine the best practice in ontology construction through mapping by considering both manual and automation approach. Key-Words: - comparative study, ontology, ontology development, ontology mapping, performance evaluation 1 Introduction Many works have been reported on the success and difficulties of ontology construction either from scratch or with the support of tools. Each claims one better than the other in terms of its performance and scalability [1], [2]. The growing number of related study indicates the importance of ontology mapping in realizing the idea of making communication on the web more meaningful. Some of the works even conduct surveys to further explore the true potential of ontology mapping and provide others with the direction in this area of investigation [3], [4]. Although the choice of approach is often debated, the approaches are actually looking at the same element. This element is the similarity or the common view between ontologies. Assessment on the quality of ontology mapping in ontology building is an important aspect to consider. Recent study shows that assessing the quality of mappings becomes main concern of ontology mapping. According to Doan [5], when tools are used for mapping two schemas or even ontology’s, there is high possibility of missing information because not all concepts are mapped between them. This paper reports on the research conducted in the area of digital cultural heritage of the traditional Malay textile (TMT). In the first stage of the research, the major challenge is in the digitizing the heterogeneity of the TMT collections which is done manually [6]. This process involves experts and individuals from related institutions before the common ontology is agreed upon. The extended work on TMT Knowledge Model has resulted in the Revised TMT Knowledge Model which is then mapped to the standard ontology in cultural heritage domain, CIDOC CRM. Then, similar mappings between both ontologies are performed using selected mapping tools. The selection of tools is based on pre-defined categories and pragmatic design criteria. Thus, this study aims to construct and analyze the mapping results between both ontologies by means of two approaches: manual and automation. Therefore, the comparative study is carried out to see whether using manual or automation approach will return similar output and the result will be used as an evidence of comparison. The remainder of this paper is organized as follows. Section 2 summarizes the previous work concerning manual and automation approach which related to the study. The description of the approach used is explained in Section 3. Section 4 then presented the experimental results and further discussion on quality of mappings. The paper concludes with Section 5 that discusses the anticipated future work directions. 2 Related Work [3] identifies two distinct architectures, namely shared ontology and heuristics, and machine learning approach. We provide some background Recent Researches in Communications, Information Science and Education ISBN: 978-1-61804-077-0 73