2021, Vol., No.70

The Korean Journal of Archival Studies 2023 KCI Impact Factor : 0.98

pISSN : 1229-7941 / eISSN : 2671-7891
https://journal.kci.go.kr/ksas

Administrative information dataset records produced by various systems designed for work are difficult to manage on a case-by-case basis, requiring separate procedures to identify and evaluate data-sets. Identified data set records are apprasal and transferred to the records management system or disposed of. In this process, sufficient records management elements must be reflected in the production system itself in order to adhere to the principles of record management. In this paper, the functional requirements of the production system to accurately identify and safely manage data-sets were derived and applied based on the case of the KR property management system. It is hoped that this research on functional requirements of production systems will be added to lead to the creation of standards for functional requirements of data set production systems.

After the revision of the Enforcement Decree of the Public Records Act, the archives created a management standard table for data set records management and performed management and control. Therefore, in this study, the data set record identification procedure and evaluation index were developed for systematic data set record management of archives. By applying this, a management standard table was prepared after identifying the records of 8 datasets in kr’s electronic procurement system, and the evaluation was carried out according to the evaluation index, and the retention period, transfer, and collection were determined. It is hoped that this case study will be of practical use to the archives at a time when concrete examples of procedures for the management of dataset records are lacking.

The purpose of this study is to investigate and analyze the current status of unit tasks, unit task operation, and record management problems used by local governments, and to present improvement measures using text-based big data technology based on the implications derived from the process. Local governments are in a serious state of record management operation due to errors in preservation period due to misclassification of unit tasks, inability to identify types of overcommon and institutional affairs, errors in unit tasks, errors in name, referenceable standards, and tools. However, the number of unit tasks is about 720,000, which cannot be effectively controlled due to excessive quantities, and thus strict and controllable tools and standards are needed. In order to solve these problems, this study developed a system that applies text-based analysis tools such as corpus and tokenization technology during big data analysis, and applied them to the names and construction terms constituting the record management standard. These unit task operation support tools are expected to contribute significantly to record management tasks as they can support standard operability such as uniform preservation period, identification of delegated office records, control of duplicate and similar unit task creation, and common tasks. Therefore, if the big data analysis methodology can be linked to BRM and RMS in the future, it is expected that the quality of the record management standard work will increase.