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Research on Development of Support Tools for Local Government Business Transaction Operation Using Big Data Analysis Methodology

  • The Korean Journal of Archival Studies
  • 2021, (70), pp.85-117
  • DOI : 10.20923/kjas.2021.70.085
  • Publisher : Korean Society Of Archival Studies
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : September 30, 2021
  • Accepted : October 23, 2021
  • Published : October 31, 2021

KIMDABEEN 1 Lee Eun Jung 2 ryu hanjo 3

1한국외국어대학교
2한성대학교
3명지대학교

Accredited

ABSTRACT

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.

Citation status

* References for papers published after 2023 are currently being built.