• 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.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.4
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• pp.251-266
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• 2013

By the progress of informatization, the data which is involved in the administration and public organizations are increased the requestion of the utilization. Nevertheless most of the agencies could not actively participate in sharing and opening the data to the public because of data quality problems. The purpose of this study is to verify the relationship for data quality, managerial and organizational factors which is to derive at the level of the organization's data quality management success factors suggested in previous studies, and the acceptance of the organization's quality management. The result identify that organizational factors, organization's data quality management encouragement and support, give effect data quality through the acceptance of data quality management. However, managerial factors was no effect the data quality management acceptance. This study than managerial approach when considering the quality control for the public organizations, in the early days of the current situation of a company-wide consensus was required, as well as directly to the level of quality factors affecting the quality of acceptance is presented to derive but has significance.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.971-977
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• 2021

The purpose of this research paper is: (1) to describe the service quality index; (2) describe the data quality index; and (3) describe the anti-corruption index of BPS Trenggalek, Indonesia. The approach chosen is quantitative with the type of survey research. The primary data collection technique was mainly based on a questionnaire distributed to 40 respondents, namely BPS service users in 5 (five) categories: the private sector, the banking industry, academics, offices, or agencies in Trenggalek Regency and universities. The results showed that the quality of BPS services was good and the data quality index where the respondents were satisfied with the data presented by BPS. Meanwhile, testing the anti-corruption index shows that BPS Trenggalek is very anti-corruption in providing services to consumers. The findings of this study suggested that to improve service quality, it is necessary to pay attention to several aspects, including published service requirements, easy requirements to be fulfilled, published procedure information, clear service process flow, published service times, and costs/tariffs are communicated. This study suggests updating data, data relevance, data accessibility, and data completeness to improve data quality. Furthermore, to maintain the very anti-corruption predicate, this study suggests maintaining service by upholding the prevailing ethics and norms.

• Asian Journal for Public Opinion Research
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• v.7 no.1
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• pp.57-74
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• 2019

Researchers usually examine the quality of survey data by several conventional measures of reliability and validity. However, those measures are mainly designed to examine the quality of an individual measurement, rather than the quality of a data set as a whole. There is a relative lack of methods for evaluation of the overall data quality. This paper attempts to fill this gap. We propose using interviewers' assessments as one of criteria for evaluating the overall data quality. Interviewers are the ones who literally conduct and thus directly observe interviews. Taiwan's Election and Democratization Studies (TEDS) have required interviewers to assess how trustworthy the responses of each of their interviewees are, and to provide several descriptions about the process and environment of the interviews. We use this information to evaluate the data quality of TEDS surveys and compare it with the results from the conventional test-retest method. The findings are that the interviewer assessment is a fair indicator of the overall reliability of attitudinal questions but not a good indicator when factual questions are examined. Regarding the evaluation of data validity, more data is required to see whether or not interviewers' assessment is informative in terms of data quality.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.91-112
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• 2019

The IoT environment has led to explosive growth of existing enterprise data, and how to utilize such big data is becoming an important issue in the management field. In this paper, major factors affecting the decisions of companies to utilize big data have been studied. And also, the effect of big data utilization on the management quality is studied empirically. During this process, we have studied the difference according to the award of Korean national quality award. As a result of the study, we confirmed that the five factors such as cost from technology, organization and environment perspective, compatibility, company size, chief officer support, and competitor pressure are key factors influencing big data utilization. Also, it was confirmed that the use of big data for management activities has an important influence on the six management quality factors based on MBNQA, and that the management quality level of Korean national quality award companies is relatively high. This paper provides practical implications for companies' use of big data because it demonstrates for the first time that big data utilization has an impact on management quality improvement.

• The Journal of Bigdata
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• v.6 no.1
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• pp.161-178
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• 2021

The importance of 'Big Data' is increasing to the point that it is likened to '21st century crude oil'. For smart city IoT data, attention should be paid to quality control as the quality of data is associated with the quality of public services. However, data quality indicators presented through ISO/IEC organizations and domestic/foreign organizations are limited to the 'User' perspective. To complement these limitations, the study derives supplier-centric indicators and their priorities. After deriving 3 categories and 13 indicators of supplier-oriented smart city IoT data quality evaluation indicators, we derived the priority of indicator categories and data quality indicators through AHP analysis and investigated the feasibility of each indicator. The study can contribute to improving sensor data quality by presenting the basic requirements that data should have to individuals or companies performing the task. Furthermore, data quality control can be performed based on indicator priorities to provide improvements in quality control task efficiency.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.249-275
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• 2003

In companies competing for today's information society, Data quality deterioration is causing a negative influence to generate company competitiveness fall and new cost. A lot of Preceding study about data qualify have been proceeded in order to solve a problem of these data qualify deterioration. Among the sides of data qualify, it has been studied mainly on qualify of the data valve and quality of data service that are the results quality concept. However. this study studied structural qualify of the data which were cause quality concept in a viewpoint of meta data management and presented data quality management maturity model through this. Also empirically this study verified that data quality improved if the management level matured.

• 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.