• International conference on construction engineering and project management
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• 2015.10a
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• pp.284-288
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• 2015

Recently, the mandate on utilizing BIM implemented by public institutions of many countries has great impact on the significantly increasing practices of BIM. The improvement of work efficiency and productivity, which is occurred by BIM adoption, depends on the consistency and accuracy of data. To maximize the benefit of BIM, the interests in BIM data quality have been enlarging all over the world. The BIM data quality pre-check, which is conducted by designer in the design phase, offers opportunities for quality improvement by continuously assessing BIM data. However, BIM quality pre-check is being conducted under arbitrary interpretation of users because of the absence of specific review factors and assessment methods for checking BIM quality. The purpose of this study is to establish an automated BIM quality pre-checking system to improve BIM design quality effectively and efficiently. It could be expected to meet the owner's requirements and to minimize the cost and time occurred additionally from revising and reproducing data by constructing consistency and accuracy of it.

• Quality Improvement in Health Care
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• v.8 no.2
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• pp.186-207
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• 2001

Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.

• Information Systems Review
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• v.10 no.1
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• pp.91-113
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• 2008

Recently, as most functional business activities in an enterprise are supported by computerized information systems, data duplication and inconsistency among functional information systems become serious problems. It brings people to have many interests on data quality management. This paper presents a case study in which a company had improved their data quality by enhancing their data quality management processes. Though the case study, we describe main issues and risk factors in the process of data quality improvement projects as well as solutions to resolve the issues, which can be referred by other companies who pursue data quality improvement. Also, the improvement effects are evaluated by multidimensional perspectives which include quantitative and qualitative measures on data quality, productivity, customer satisfaction, organization, and culture.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.3
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• pp.277-289
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• 2021

Among various data types obtained from the ocean, the quality controls for abiotic data collected from chemical, physical, and geological field surveys haves already been partially established. Due to the difficulties in standardization of the data collections and basic analyses, however, the quality controls of biotic data are in its early stage. For marine fish, the necessity of quality control is more demanded due to the wide range of data usage, but there are currently no consistent quality control guidelines because of the diversity and scope of data types derived from species-specific and age-specific information throughout various habitats. In this paper, we provide examples of marine fish data utilization and also show methods of the marine fish data collection, limitations of the data collection methods, and suggestions for improving the marine fish data quality. We hope this paper will help to establish the direction of quality control for marine fish data from both fishery-dependent and fishery-independent surveys in Korea in the near future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.689-699
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• 2013

During extreme ionospheric storms, anomalous ionospheric delays and gradients could cause potential integrity threats to users of GNSS (Global Navigation Satellite System) augmentation systems. GNSS augmentation ground facilities must monitor these ionospheric anomalies defined by a threat model and alarm the users of safely-of-life applications within time-to-alerts. Because the ionospheric anomaly threat model is developed using data collected from GNSS reference stations, the use of poor-quality data can degrade the performance of the threat model. As the total number of stations increases, the number of station with poor GNSS data quality also increases. This paper analyzes the quality of data collected from Korean GPS reference stations using comprehensive GNSS data quality check algorithms. The results show that the range of good and poor qualities varies noticeably for each quality parameter. Especially erroneous ionospheric delay and gradients estimates are produced due to poor quality data. The results obtained in this study should be a basis for determining GPS data quality criteria in the development of ionospheric threat models.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.3
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• pp.56-65
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• 2001

In interpreting stream water quality data, scientific or statistical mehtods should be employed. Classical parametric statistical methods may not be adopted in analyzing water quality data, due to the violation of normality. In this study, nonparametric statistical methods, such as Kruskal-Wallis test and Mann-Whitney test, were used in comparing water quality data from several monitoring stations. Water quality data used are those collected Bokha watershed, located in Ichon-city, Kyonggi province. Based on the test results, domestic sewage is the major pollution source. A couple of sub-watersheds with a large number of livestock do not show significant differences in water quality parameters. It should be noted that comparison of mean values of water quality parameters is difficult to relate water quality with watershed characteristics. The results also indicate that livestock farming does not significantly affect the water quality.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.25-40
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• 2022

This study is about how the quality of M2M big data that provides real-time information affects users. Recently, there are many difficulties in acquiring and managing data because data types such as variety, data volume, and data velocity are changing rapidly and diversified. This not only leads to a decrease in data quality but also it can give a negative impact when making decisions using data. Generally, the quality of data is defined as 'suitability for use', which means that data quality must meet the expectations of user needs. Therefore, data providers need activities to improve data quality for this purpose, and the key is to identify data quality dimensions in each field where data is used and provide data suitable for the level of user needs. In this study, the relationship between the quality area of real-time M2M data used in the traffic information system and user satisfaction was analyzed. Research models and hypotheses were established to analyze the effects between variables related to M2M big data. In order to test the hypothesis, a causal relationship between the major factors was identified by conducting a survey and analyzing the data users.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.119-128
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• 2007

In this paper, We study on the Data Quality Model of ISO/IEC 25012 among the Software product Quality Requirements and Evaluation(SQuaRE) in ISO/IEC 25000 Series. Because of the increasing data, user require the accuracy data, recent data, suitable data for used tools, complied security and not open to be public. We research the data quality management in the point of application of be affect influenced low quality in business. We propose the testing items and we propose the method of the evaluation proposed testing items. We study on the basis international Standards ISO/IEC 25012 and ISO/IEC 9126-2 and we proposed the testing method quantitatively on the basis of ISO/IEC 25000.

• The Journal of Society for e-Business Studies
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• v.14 no.3
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• pp.39-57
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• 2009

As electronic commerce becomes more common and the data volume of e-catalog increases, a systematic approach to data quality management is being required. Upon the necessity, we propose a process-based framework for e-catalog data quality management. This is the methodology for data management and improvement activities continuously performed to satisfy the expectation of industry to e-catalog systems. In the framework, contents for quality management consist of data, quality management items, and quality management processes. These are again subdivided according to organization levels, i.e, user, data administrator, and chief information officer.

• Journal of Korean Society for Quality Management
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• v.23 no.1
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• pp.64-73
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• 1995

At the time of internationalization, it is inevitable to improve the quality of products to survive the international competition. ISO 9000 series have been recognized by most companies as the quality assurance system. However, it was known to require quite many records and data which need to be controlled and analyzed. The objective of this paper is to present the procedure in establishing the quality information data base which enables a company to easily handle the required records and data for the ISO 9000 series. Examples using the quality information data base are also presented.