• The Korean Journal of Archival Studies
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• no.52
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• pp.119-170
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• 2017

This study aims to analyze the environment for the open-source records system and to identify the risk and requirements for the success of the strategy in Korea. For this, Chapter 2 presented a review of the strategic benefits of open source to public organizations, developers, and users. It also discussed the process of cooperatively developing and releasing the source code and the technology infrastructure supporting open source. In Chapter 3, six representative open-source projects in the field of records management were selected, and case studies were conducted. To derive comprehensive implications, we have divided the main development body of open-source projects into international organizations, international cooperation systems, national archives, and software development companies. We also analyzed the background and purpose of each project, the agents of development and funding, the governance model, the development period and cost, the business model and software architecture, the community composition, and the licensing strategy. Through this, we have derived four critical success factors. In terms of technology, a component-based design was required; therefore, we proposed a microservice architecture and a model-view-controller design pattern. Next, it was necessary to reestablish system requirements of records center and archives. Moreover, we also proposed a dual licensing strategy to allow developers to easily participate in open-source projects. Lastly, we emphasized a strong governance structure and an effective cooperation framework to create a sustainable community. For a record system to be open-source successfully in an organization-centered market, the roles of software developers and end users should be exercised more in the community. To achieve this, it is important to build various collaborative tools and development infrastructure from a planning stage to a centralized one.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.79-88
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• 2021

In this paper, we propose a API Gateway technique for the expansion of human resource management module, one of the ERP functions. The institution has introduced ERP (Enterprise Resource Planning) based on its efforts to transform all human and physical resources into business competitiveness and its response to the digital knowledge informatization environment, and listed it as multiple success factors. Human resource management is one of the factors that have been dealt with. However, ERP's Human Resources Management Module remains in the role of functional personnel management. How to utilize human resources begins with navigating and recognizing human resources. The proposed API Gateway technique leverages blockchain networks to design and implement APIs for human resource sharing and navigation, including the possibility of extending ERP's human resource management module. Secondly, it was designed and implemented using a smart contract that behaves like an API for preventing information forgery. The proposed method will not only be used as a tool that can actively utilize human resources, but will also be a complete resource for utilizing big data technology.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.35-44
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• 2023

In recent, there are many research cases that analyze trends or research trends with text analysis. When collecting documents by searching for keywords in abbreviations for data analysis, it is necessary to disambiguate abbreviations. In many studies, documents are classified by hand-work reading the data one by one to find the data necessary for the study. Most of the studies to disambiguate abbreviations are studies that clarify the meaning of words and use supervised learning. The previous method to disambiguate abbreviation is not suitable for classification studies of documents looking for research data from abbreviation search documents, and related studies are also insufficient. This paper proposes a method of semi-automatically classifying documents collected by abbreviations by going topic modeling with Non-Negative Matrix Factorization, an unsupervised learning method, in the data pre-processing step. To verify the proposed method, papers were collected from academic DB with the abbreviation 'MSA'. The proposed method found 316 papers related to Micro Services Architecture in 1,401 papers. The document classification accuracy of the proposed method was measured at 92.36%. It is expected that the proposed method can reduce the researcher's time and cost due to hand work.