Earticle

초록

영어

The government has recently undertaken various initiatives aimed at enhancing the performance management system of the national data infrastructure. Specifically, to bolster the dataherb’s and datacenter’s roles and enhance the value of data use, the allocation of performance indicators was increased, the ratio of returning companies was incorporated, and additional best use case indicators were provided. Moreover, the operational base of the current system is progressively enlarging as efforts to establish an additional point indicator for stimulating dataherb operation and to adjust indicator weights in accordance with annual objectives gain momentum. The government’s initiatives play a significant role in establishing the policy groundwork for advancing data-driven administration and innovative applications across the entire industry. Nonetheless, the existing performance management system fails to adequately account for the unique characteristics of each dataherb. It is also limited by the absence of a multidimensional performance evaluation framework that incorporates both qualitative and quantitative measures. Accordingly, this investigation proposes a novel model for managing multidimensional indicators to enable more precise and ongoing measurement of data management performance at the national level. By creating an assessment system that incorporates multiple indicators, the proposed model seeks to ensure that dataherb performance can be analyzed and compared in a balanced manner. This study is significant for improving the objectivity and reliability of performance management regarding national data infrastructure, greatly increasing the value derived from data usage, and aiding in evidence-based assessments of policy impacts.

목차

Abstract
1. INTRODUCTION
2. CURRENT STATUS OF THE DATA INDUSTRY OF KOREA
3. EFFORTS OF THE DATA INDUSTRY OF KOREA
4. MULTIDIMENSIONAL DESIGN FOR PERFORMANCE INDICATORS
4.1. Upholding the Current Performance Management Indicators
4.2. Designing the Multidimensional Performance Management Indicators
4.3. Direction of Multidimensional Indicators for National Data Management
5. CONCLUSIONS
Acknowledgement
REFERENCES

키워드

저자

• Suck-Tae JOUNG [ Professor, Department of Computer & Software Engineering, Wonkwang University (AI Convergence Research Institute), Republic of Korea ]
• Hyunsup AHN [ Project Owner, Department of Location Service, Search and Geocoding, HERE Technologies, Germany ]
• Sangwon LEE [ Professor, Department of Computer & Software Engineering, Wonkwang University (AI and Bigdata Convergence Research Center, AI Convergence Research Institute), Republic of Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Culture Technology(IJACT)

• 간기

  계간

• pISSN

  2288-7202

• eISSN

  2288-7318

• 수록기간

  2013~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 600 DDC 700