• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1214-1217
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• 2013

오늘날 스마트 폰의 보급이 보편화 되면서 모바일 시장이 크게 성장하게 되었다. 또한 그만큼 많은 사용자들이 이용함에 따라 더 많은 양의 콘텐츠를 제공을 해야 하기 때문에 데이터는 점점 증가 할 수밖에 없는 상황이다. 하지만 잘못된 데이터 정보를 마케팅 같은 곳에 활용하여 피해를 보기 때문에 잘못된 데이터와 신뢰성 데이터를 구분을 하여 신뢰성 있는 데이터를 사용자에게 제공해야 한다. 따라서 본 논문에서는 이러한 문제점을 해결하고자 빅데이터에서 추출하는 과정에서 데이터 품질관리를 실시하고 저장된 데이터도 품질관리를 함으로써 신뢰성 있는 데이터를 생성 및 관리 할 수 있도록 하는 빅데이터 환경에서 최적화된 데이터 품질관리 시스템을 설계한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.107-108
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• 2023

자율운항선박 (Maritime Autonomous Surface Ship, MASS) 관련 기술은 전 세계적으로 활발히 개발 중이다. 이와 더불어 선박정보 통신 기술(ICT)을 활용한 선박 관리에 대한 수요가 증가하면서 선박 데이터의 신뢰성 확보가 더욱 중요해지고 있다. 선박에서 사용하는 데이터는 점차 복잡해지고 용량이 증가함에 따라 체계적인 관리 방안이 필요하다. 본 연구에서는 주요 선급에서 발간한 기술자료와 표준동향 분석 및 전문가 논의를 통해 신규 표준 아이템을 도출하였다. 이를 기반으로 ISO 선박 및 해양기술 분과에 제안한 선박 데이터 신뢰성 확보를 위한 데이터 품질 관리 표준 제안한 결과를 소개하고자 한다. 신규 제안한 표준을 통해 국내 조선소 및 기업에서 개발한 선박 성능 분석 및 모니터링 시스템에 대한 품질 검증에 활용할 수 있을 것으로 예상된다.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.83-105
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• 2013

There are two ways to assess data quality : measurement of data itself and assessment of data quality management process. Recently maturity assessment of data quality management process is used to ensure and certify the data quality level of an organization. Following this trend, the paper presents the process reference model which is needed to assess data quality management process maturity. First, the overview of assessment model for data quality management process maturity is presented. Second, the process reference model that can be used to assess process maturity is proposed. The structure of process reference model and its detail processes are developed based on the process derivation approach, basic principles of data quality management and the basic concept of process reference model in SPICE. Furthermore, characteristics of the proposed model are described compared with ISO 8000-150 processes.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.473-478
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• 2007

본 연구는 데이터 품질개선을 위해 사용자들에게 베타데이터 관리 시스템 사용의도에 영향을 줄 수 있는 주요 요인들이 무엇이 있는지 식별해보고 요인간의 관련성을 분석 하였다. 최근 이슈화고 있는 Data Architecture, Data Integration, Data Quality 프로젝트를 계획 또는 경험이 있는 조직 IT담당자들을 대상으로 메타데이터 관리 시스템 사용의도 설문을 하였고, SPSS를 이용하여 통계적 희귀분석을 수행하였다. 분석에서 이를 설명하는 연구모형으로 정보기술수용모델(Technology Acceptance Model:TAM)을 적용하였으며, 사용 용이성(Perceived easy of use), 유용성(perceived usefulness)에 영향을 주는 외생변수로는 개인의 데이터 품질개선의도, 동기부여, 조직의 지원 등으로 나타났다. 분석결과 데이터품질 개선의도가 시스템 사용의도에 영향이 있음을 실증하였고, 사회적 요인(동기부여, 조직의 기원) 모두 유용성에는 영향을 미쳤으나 사용 용이성에는 유의하지 많은 결과를 보였다. 이 연주에서는 조직이 데이터 품질 개선을 위해 메타데이터 관리시스템을 사용하고자 할 경우 고려사항과 향후 사용자 관점의 기술수용들을 확장된 연구를 수행하여 데이터품질 개선에 방안들을 탐색할 것을 제안하였다.

• Digital Contents
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• no.1 s.140
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• pp.24-25
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• 2005

지난해 9월에 발족된 데이터품질관리포럼이 창립 3개월여만에 국내 주요 금융사와 공공기관을 아우르는 모임으로 발돋움했다. 특히 KT, 우리 금융, 신한 은행등과 같은 국내 굴지의 기업들이 포럼에 적극 참여해 활발히 활동하면서 관련 업계의 큰 관심을 끌고 있다. 데이터 품질관리 포럼 이정우 회장(연세대 교수)을 만나 포럼의 활동 목표의 운영 방향에 대해 들어 봤다. 다음은 이정우 회장과의 일문 일답

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.79-99
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• 2010

As data exchange between business partners in e-business becomes more active, obtaining and managing reliable data is emerging as a pressing issue for corporations and organizations. For the resolution of data quality, this paper proposes a framework for data quality management with its scenario. The data quality management framework consists of three phases: data quality monitoring, data quality improvement and data application, each of which has three processes. In each process, necessity, functions, roles, and relationships among processes are specified. In order for users to directly apply the framework to the business field, a business scenario is given with examples of product identification and classification code systems widely used in e-business.

• The Korean Journal of Archival Studies
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• no.71
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• pp.237-272
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• 2022

In 2019, the pilot project to establish a record management system for administrative information datasets started in earnest under the leadership of the National Archives. Based on the results of the three-year project by 2021, the improved administrative information dataset management plan will be reflected in public records-related laws and guidelines. Through this, the administrative information dataset becomes the target of full-scale public record management. Although public records have been converted to electronic documents and even the datasets of administrative information systems have been included in full-scale public records management, research on the quality requirements of data itself as raw data constituting records is still lacking. If data quality is not guaranteed, all four properties of records will be threatened in the dataset, which is a structure of data and an aggregate of records. Moreover, if the reliability of the quality of the data of the administrative information system built by reflecting the various needs of the working departments of the institution without considering the standards of the standard records management system is insufficient, the reliability of the public records itself can not be secured. This study is based on the administrative information dataset management plan presented in the "Administrative Information Dataset Recorded Information Service and Utilization Model Study" conducted by the National Archives of Korea in 2021. A study was conducted. By referring to various data, especially public data-related policies and guides, which are being promoted across the government, we would like to derive quality evaluation requirements in terms of records management and present specific indicators. Through this, it is expected that it will be helpful for record management of administrative information dataset which will be in full swing in the future.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.217-222
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• 2020

This study is about the data quality management evaluation model. As the information and communication technology is advanced and the importance of storage and management begins to increase, the guam feeling for data is increasing. In particular, interest in the fourth industrial revolution and artificial intelligence has been increasing recently. Data is important in the fourth industrial revolution and the era of artificial intelligence. In the 21st century, data will likely play a role as a new crude oil. It can be said that the management of the quality of this data is very important. However, research is being conducted at a practical level, but research at an academic level is insufficient. Therefore, this study examined factors affecting data quality management for experts and suggested implications. As a result of the analysis, there was a difference in the importance of data quality management.

• The Journal of Bigdata
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• v.3 no.1
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• pp.33-40
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• 2018

With the advent of the fourth industrial revolution, each industry has been innovated with new concepts. New concept of each industry takes advantage of new information technologies based on big data infra. Thus quality control of big data is becoming more important. In this paper, we try to develop a framework of big data service quality through a case study. A 'Legal Tech' service was selected for the case study. Especially a big data quality framework was developed for a living law service in the Ministry of Justice.

• The Journal of Bigdata
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• v.2 no.2
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• pp.87-93
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• 2017

The research on data quality has been performed for a long time. However, the research focused on structured data. With the recent digital revolution or the fourth industrial revolution, quality control of big data is becoming more important. In this paper, we analyze and classify big data quality types through previous research. The types of big data quality can be classified into value, data structure, process, value chain, and maturity model. Based on these comparative studies, this paper proposes a new standard, service quality of big data.