This content below is combined from several research and work; the author would like to thank the all sources for providing this useful information. And thank you UTCC for funding the research for all these past years.
Tthe object model is the center of data modeling; on the other hand ontology itself has the concept which is the basis of knowledge base. The goal of the data model is to certify that all data objects required by the database are completely and accurately represented. Because the data model uses easily understood notations and natural language, it can be examined and confirmed as correct by the end-users. Ontologies are objects of interest (universal of discourse).
Ontology describes the types of things that exist, and rules that govern them; a object model defines records about things, and is the basis for a database design. Not all the information in ontology may be needed (or can even be held) in a data model and there are a number of choices that need to be made (West, M., 2006).
Ontologies are promised to bright future. This paper proposes that as ontologies are closely related to modern object oriented software engineering, it is natural to adapt existing object-oriented software development methodologies for the task of ontology development. This is some part of similarity between descriptive ontologies and database schemas, conceptual data models in object oriented are good applicant for ontology modeling, however; the difference between constructs in object models and in current ontology proposals which are object structure, object identity, generalization hierarchy, defined constructs, views, and derivations. We can view ontology design as an extension of logical database design, which mean that the training object data software developers could be a promising approach. An ontology is the comparable of database schema but ontology represent a much richer information model than normal database schema, and also a richer information model compared to UML class/object model. Object modeling focus on identity and behavior is completely different from the relational model’s focus on information.
It is likely to adjust existing object oriented software development methodologies for the ontology development. The object model of a system consists of objects, identified from the text description and structural linkages between them corresponding to existing or established relationships. The ontologies provide metadata schemas, offering a controlled vocabulary of concepts. At the center of both object models and ontologies are objects within a given problem domain. The difference is that while the object model should contain explicitly shown structural dependencies between objects in a system, including their properties, relationships, events and processes, the ontologies are based on related terms only. On the other hand, the object model refers to the collections of concepts used to describe the generic characteristics of objects in object oriented languages. Because ontology is accepted as a formal, explicit specification of a shared conceptualization, we can naturally link ontologies with object models, which represent a system oriented map of related objects easily.