OASIS(Oriental Medicine Advanced Searching Integrated System) provides the information on research articles of Korean Medicine. This study aims to propose an article construction system that can manage massive metadata of articles efficiently by analyzing its repetitive input procedure. Since the articles are provided in the form of public data that can used by everyone, metadata of the articles should be constructed correctly. In the past, the metadata had been entered in three steps. Thus, it takes a lot of time to input the metadata, and many errors occur during the steps. To solve these problems, we in this paper developed an article construction system that the metadata can be corrected by preventing users’ input mistakes. After a PDF file is uploaded in this system, the publication information of the journal is extracted automatically from the file name of the PDF. Then, other metadata is entered and metadata input of the article is completed. By using the article construction system, absolute task time for constructing the information of article database was reduced and metadata input errors were prevented. In the future, we will demonstrate the performance of our system through empirical research so that other related systems can utilize the method of this system.