• Title/Summary/Keyword: 데이터 품질기준

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Selection Criteria of Target Systems for Quality Management of National Defense Data (국방데이터 품질관리를 위한 대상 체계 선정 기준)

  • Jiseong Son;Yun-Young Hwang
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.155-160
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    • 2023
  • In principle, data from all databases and systems managed by the Ministry of Defense or public institutions must be guaranteed to have a certain level of quality or higher, but since most information systems are built and operated, data quality management for all systems is realistically limited. Most defense data is not disclosed due to the nature of the work, and many systems are strategically developed or integrated and managed by the military depending on the need and importance of the work. In addition, many types of data that require data quality management are being accumulated and generated, such as sensor data generated from weapon systems, unstructured data, and artificial intelligence learning data. However, there is no data quality management guide for defense data and a guide for selecting quality control targets, and the selection criteria are ambiguous to select databases and systems for quality control of defense data according to the standards of the public data quality management manual. Depends on the person in charge. Therefore, this paper proposes criteria for selecting a target system for quality control of defense data, and describes the relationship between the proposed selection criteria and the selection criteria in the existing manual.

A Proposal of Evaluation of Large Language Models Built Based on Research Data (연구데이터 관점에서 본 거대언어모델 품질 평가 기준 제언)

  • Na-eun Han;Sujeong Seo;Jung-ho Um
    • Journal of the Korean Society for information Management
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    • v.40 no.3
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    • pp.77-98
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    • 2023
  • Large Language Models (LLMs) are becoming the major trend in the natural language processing field. These models were built based on research data, but information such as types, limitations, and risks of using research data are unknown. This research would present how to analyze and evaluate the LLMs that were built with research data: LLaMA or LLaMA base models such as Alpaca of Stanford, Vicuna of the large model systems organization, and ChatGPT from OpenAI from the perspective of research data. This quality evaluation focuses on the validity, functionality, and reliability of Data Quality Management (DQM). Furthermore, we adopted the Holistic Evaluation of Language Models (HELM) to understand its evaluation criteria and then discussed its limitations. This study presents quality evaluation criteria for LLMs using research data and future development directions.

Improving data quality through Data Owners management (데이터 오너 관리를 통한 데이터 품질 향상)

  • Park, Ji-Soo
    • Annual Conference of KIPS
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    • 2007.11a
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    • pp.278-281
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    • 2007
  • 데이터 품질 기준은 반드시 현업의 입장에서 바라봐야 하며, 현업의 마인드가 데이터 품질에 가장 결정적인 영향을 미친다. 이에 따라 데이터 품질을 향상시키기 위해서는 현업이 데이터 품질 관리에 직접 참여할 수 있는 연구가 필요하다. 본 연구에서는 데이터 값(Data Value)에 대한 데이터 오너 (Owner)를 부여하여 데이터 품질 오류 시 현업이 직접 데이터 품질 관리 프로세스에 참여 할 수 있는 방안을 제시하였다. 데이터 품질 관리 프로세스는 데이터 품질 대상 및 기준을 정의하고 측정, 분석, 개선하는 방법이다. 본 연구에서 제시한 데이터 오너 관리 방안은 보다 효율적인 데이터 품질 관리 프로세스를 개선 시킬 수 있을 것이다.

An Empirical Analysis on the Effect of Data Quality on Economic Performance in the Financial Industry (금융산업에서의 데이터 품질이 경제적인 성과에 주는 영향의 실증분석)

  • Lee, Sang-Ho;Park, Joo-Seok;Kim, Jae-Kyeong
    • Information Systems Review
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    • v.13 no.1
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    • pp.1-11
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    • 2011
  • This study empirically investigated the effect of firm-level data quality on economic performance in the Korean financial industry during 2008~2009. The data quality was measured by data quality management process index and data quality criteria by Korea Database Agency, and financial firm performance data was acquired from Financial Statistics Information System of the Financial Supervisory Service. The result showed that the data quality has statistically significant impacts on financial firm performance such as sales, operating profit, and value added. If the data quality management process index increases by one, the value added can increase by 2.3 percent. Moreover, the data quality criteria increase by one, the value added can increase by 72.6 percent.

항로표지 데이터 품질지수 산출에 관한 연구

  • 정제한;한윤석;이예경;다이리;탕멍위엔;장준혁;신상문
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.100-102
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    • 2022
  • 데이터의 품질을 파악하고 그 기준을 선정하는 것은 해양 항로 표지와 같은 분석에 있어서 중요한 역할을 한다. 본 연구에서는 해양 분야에서 디지털 항로표지 데이터의 품질 진단을 위해 공정능력지수를 이용하여 데이터의 품질을 정량적으로 산출하고 그 결과에 대한 판정 기준을 명확히 하여 데이터에 대한 품질을 판단할 수 있는 척도를 제시하였다.

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Standardization of Data Quality and Management Regulation for Korean CORS (국내 GNSS 상시관측소 데이터 품질 및 관리규정 표준화에 관한 연구)

  • Jin Sang, Hwang;Hyuk Gil, Kim;Hong Sik, Yun;Jae Myoung, Cho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.245-258
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    • 2015
  • This study aimed to conduct the standardization of various specifications for determining the proper construction and operation of domestic CORS (Continuously Operating Reference Station). To achieve the plan, the standardization was proposed for various compositions of CORS, such as the data quality, structure, and equipment. Also, we have studied the method for empirically determining the reference values of QC (Quality Check) of CORS data. Those large amounts of samples for each QC index values were built to approach in empirical and statistical methods. In fact, those general and recommended reference values were determined from analyzing the sample distributions, using the empirical and statistical approaches. The result is expected to be utilized for a variety of research fields for standardization, accurate data acquisitions and service operations for the domestic CORS

Establishing Data Quality Metric from Dirty Data (오류 데이터로부터의 데이터 품질 메트릭의 정립)

  • 김수경;최병주
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10a
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    • pp.409-411
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    • 2000
  • 소프트웨어 제품의 품질을 보증하는 일은 매우 중요하며, 국제 표준인 ISO/IEC9126은 소프트웨어 품질 특성 및 측적 메트릭 표준을 제공하고 있다. 이때 ISO/IEC 9126에서는 소프트웨어를 프로그램, 절차, 규칙 및 관련문서로 한정하고 있기 때문에 데이터의 품질에는 적용할 수 없다. 본 논문에서는 데이터 품질 평가 및 제어를 위하여 오류 데이터 형태를 분류하고, 이를 기반으로 데이터 품질 특성을 추출한다. 추출된 데이터 품질 특성을 측정하기 위해, 오류 데이터를 품질 속성으로 하는 데이터 품질 특성을 추출한다. 본 논문에서 제시하는 데이터 품질 메트릭은 지식 공학(knowledge engineering) 시스템이 최종 사용자에게 제공하는 데이터나 지식의 품질 측정 및 제어에 기준이 된다.

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Extraction of Data Quality Characteristics from Dirty Data (데이터 오류에서 추출한 데이터 품질 특성)

  • 김수경;최병주
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04a
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    • pp.549-551
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    • 2000
  • 소프트웨어 제품의 품질을 보증하는 일은 매우 중요하며, 국제표준인 ISO/IEC 9126은 소프트웨어 품질 및 특성 및 측정 메트릭 표준을 제공하고 있다. 이때 ISO/IEC 9126에서는 소프트웨어를 프로그램, 절차, 규칙 및 관련문서로 한정하고 있기 때문에 데이터의 품질에는 적용할 수 없다. 본 논문에서는 데이터 품질 평가 및 제어를 위하여 데이터 오류 형태를 분류하고, 이를 기반으로 데이트 품질 특성 및 부특성을 분류한다. 데이터 품질 특성 분류는 ISO/IEC 9126에 정의한 소프트웨어 품질 특성을 데이터 오류 형태에 대응시켜 추출한다. 본 논문에서 제시하는 데이트 품질특성 분류는 지식 공학(knowledge engineering)시스템이 최종 사용자에게 제공하는 데이터나 지식의 품질 측정 및 제어에 기준이 된다.

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A study of Multimedia Data Quality Evaluation Metrics of the Game (게임의 멀티미디어 데이터 품질평가지표 연구)

  • Yoon, Seon-Jeong
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.9
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    • pp.63-70
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    • 2013
  • The multimedia data of game affects the immersion of the game depending on its quality. It is difficult to design the evaluation criteria of artistic quality of the data. But, in a technical point of view, it is possible to evaluate its quality. Thus, the design of evaluation standard can ensure the reliability and objectivity of quality. However, multimedia data quality evaluation metrics had not yet been designed. Therefore, in this study, we extracted quality evaluation elements of Game Multimedia Data, and verified the reliability of the elements. And we defined detailed evaluation items of each element, developed Multimedia Data Quality Evaluation Metrics. We expect that the results of this study will serve as a guide in the development of high-quality games, have a positive impact on the growth of the game industry.

Proposal of Public Data Quality Management Level Evaluation Domain Rule Mapping Model

  • Jeong, Ha-Na;Kim, Jae-Woong;Chung, Young-Suk
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.189-195
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    • 2022
  • The Korean government has made it a major national task to contribute to the revitalization of the creative economy, such as creating new industries and jobs, by encouraging the private opening and utilization of public data. The Korean government is promoting public data quality improvement through activities such as conducting public data quality management level evaluation for high-quality public data retention. However, there is a difference in diagnosis results depending on the understanding and data expertise of users of the public data quality diagnosis tool. Therefore, it is difficult to ensure the accuracy of the diagnosis results. This paper proposes a public data quality management level evaluation domain rule mapping model applicable to validation diagnosis among the data quality diagnosis standards. This increases the stability and accuracy of public data quality diagnosis.