隨著資訊科技發展快速，透過網路搜尋特定領域的知識已非常方便且豐富，這樣的結果乃是拜科技的便利與人員投入所賜，不過網路分享的資料過於泛濫與格式的不同，導致搜尋到的結果繁雜，不易整理，使研究者需耗費更多的時間來對搜尋到的資料再分析、擷取為資訊。但若可以在搜尋資訊的同時，能透過詳細分類和描述來定義資訊，則能幫助於領域知識上的釐清並加強研究者對整個領域的掌握，並便於爾後領域知識在網路環境上的分享與建構、維護。為了讓研究者在研讀文獻的過程中，可以掌握文獻的屬性、類別以及與文獻重要內容之間的關聯，本研究透過建立領域知識本體論，把理解領域文獻後的知識依類別、屬性，利用協同合作方式慢慢的建構一個豐富的領域知識庫。研究者可以透過知識庫來查詢領域的相關知識，並將查詢結果輔以圖形表示來協助研究者理解領域知識，讓研究者在理解領域知識的過程中可以清楚掌握領域重要物件之間的關聯，輕易的建構出相關領域的知識概念圖。 Since the information technology has been developed so fast, searching the related knowledge or information in specific domain is much easier than before. However, the amount of returning information usually too large and the relations between the handling objects are usually complicated. The users can only processing the collected objects, or documents, based on their basic properties such as document name or publishing years. It is difficult for a user to manage all the deep knowledge involved based on the information mentioned or discussed within the document. However, in order to master the overall concepts of the particular domain, it is necessary for the user to be able to actually study the article and understand the real contents of it and then, some how, to record the structures and relations of the knowledge which he has mastered after reading and understand the contents elaborated in the documents. If we can classify and describe the related information easily, it would help the researcher to grasp the whole picture of the domain and enhance the quality of his work. In this research we have shown how a researcher can improve the effectiveness of his study by easily build-up the complete domain ontology and specify the concept and the relations between the research articles in a structured way. The structure of the research domain is following a specific ontology which is determined before the experiment. The users are allowed to present the relations between the ontology objects in the articles by calculating the weightings and visualizing the arranged data and show the complete domain framework. The visualization is done by drawing relational diagrams based on the user’s query. This permits the user to master the overall concepts of the interested domain. The total framework is implemented on the web for easy accessibility. This approach of domain knowledge analysis provides more precise information about document relationships.