• Journal of Information Management
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• v.34 no.2
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• pp.67-88
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• 2003

There have been increased interests in information visualization. Information visualization has been considered as a way to summarize textual data so that the users can access large amount of data more efficiently and effectively. However, many information visualization techniques stem from scientific visualization techniques, which might be difficult for the regular users to understand. More importantly, the system models used by most of the information visualization techniques do not have real world counterpart. For example, most of the users do not represent or process the textual data in terms of fisheye view or a topological map. This means that there is no affordance on the current information visualization systems from the users point of view. In this paper, we analyzed this problem by using the user interface design principles to point out what lacks in the current information visualization systems. More specifically, we have applied Nielson's Heuristic Evaluation technique to review four representative information visualization techniques. The analysis results confirmed our original hypothesis on why the current information visualization systems are not part of the mainstream information systems. Finally, we suggested to invest more efforts in improving the currently prevalent and familiar bullet list type textual information presentation method based on the usability studies and the intelligent content analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.517-518
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• 2012

• Spatial Information Research
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• v.23 no.2
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• pp.21-29
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• 2015

Recently, according to the increasingly populated data, many media and organizations focus on big data, data visualization, information visualization and infographics. Domestically, Chosun.com and Hankyoreh online have improved on the data visualization field and internationally, the Guardian, Wall Street Journal, and New York Times are the leading companies on that area. Until now, many people have recognized infographics as a design-oriented product in Korea. However, one of significant data visualization programs, Tableau Public, can visualize data more efficiently. In this paper, Data Visualization Methods Quadrant for Policy Making is defined, and data analysis and producing infographics are executed. As used data, World Bank open source was adopted and using the number of passenger cars per 1,000 people, two analysis results are extracted. First, in high income group, the more GNI per capita, the lesser Slope is represented and in mid income group, the more GNI per capita positively affects to Slope. Second, in the global finance crisis, the car ownership rate was about 1.7 times than the usual state in the global economy. Through the case study, this paper suggests that the direction of producing infographics should be changed from design-oriented to data-oriented. Moreover, the data-oriented infographics should be propagated as means of scientific research and policy making.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.197-206
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• 2019

In this study, we analyzed the effects of data visualization education with using Python on the improvement of computing thinking ability of the 6th grade students of elementary school. Based on the results of the needs analysis of 60 elementary school teachers and 120 elementary school students, we developed the data visualization education program. In the developed educational program, 24 elementary school students were trained for 6 days and 36 hours in total. Thereafter, students were subjected to pre- and post-comparison tests. As a result of the analysis, it was found that the data visualization education with using Python is effective in improving the Computational cognition, Fluency, Originality, Elaboration of the 6th grade students in elementary school.

• Journal of The Korean Association of Information Education
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• v.23 no.4
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• pp.283-292
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• 2019

In this study, an unplugged education method which focuses on the data visualization training was applied to third grade students of an elementary school and analyzed its impact on enhancing their computational thinking. The analysis was conducted on 60 elementary school teachers and 124 third grade students and the unplugged education program based on the data visualization procedure was developed. The education program developed was carried out with 24 third grade students for 36 hours over six days. The effect of the program applied was analyzed through the pre-to-post comparison performed with perceptive strength test and creativity test in order to examine the enhancement in computational thinking. According to the analysis result, the unplugged education method which focuses on the data visualization training has significant effect on the 'computational perception' and 'creativity' of third grade students.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.363-373
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• 2022

Multi-omics data is difficult to interpret due to the heterogeneity of information by the volume of data, the complexity of characteristics of each data, and the diversity of omics platforms. There is not yet a system for interpreting to visualize research data on environmental diseases concerning environmental harmful substances. We provide MEE, a web-based visualization tool, to comprehensively explore the complexity of data due to the interconnected characteristics of high-dimensional data sets according to exposure to various environmental harmful substances. MEE visualizes omics data of correlation between omics data, subjects and samples by keyword searches of meta data, multi-omics data, and harmful substances. MEE has been demonstrated the versatility by two examples. We confirmed the correlation between smoking and asthma with RNA-seq and Methylation-Chip data, it was visualized that genes (P HACTR3, PXDN, QZMB, SOCS3 etc.) significantly related to autoimmune or inflammatory diseases. To visualize the correlation between atopic dermatitis and heavy metals, we selected 32 genes related immune response by integrated analysis of multi-omics data. However, it did not show a significant correlation between mercury in blood and atopic dermatitis. In the future, should continuously collect an appropriate level of multi-omics data in MEE system, will obtain data to analyze environmental substances and diseases.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.72-81
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• 2014

As big data are one of main issues in the recent days, the interests on their technologies are also increasing. Among several technological bases, this study focuses on data visualization and R based on open source. In general, the term of data visualization can be summarized as the web technologies for constructing, manipulating and displaying various types of graphic objects in the interactive mode. R is an operating environment or a language for statistical data analysis from basic to advanced level. In this study, a web application with these technological aspects and components is newly implemented and exemplified with data visualization for geo-based open data provided by public organizations or government agencies. This application model does not need users' data building or proprietary software installation. Futhermore it is designed for users in the geo-spatial application field with less experiences and little knowledges about R. The results of data visualization by this application can support decision making process of web users accessible to this service. It is expected that the more practical and various applications with R-based geo-statistical analysis functions and complex operations linked to big data contribute to expanding the scope and the range of the geo-spatial application.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.327-336
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• 2017

People spend most of their time in the indoor environment. Among the various indoor environmental factors, air and thermal environment directly affect human's health and efficiency of work. Therefore, efficient monitoring of indoor environment is highly important. For assisting the residents to understand the state of the indoor environment much easier and more intuitive, this paper analyze the visualization cases of the conventional indoor environment. Then explore the direction of improvement for the visualization method to propose a more effective visualization method. The approach of web and BIM(Building Information Model)-based visualization of indoor environment proposed in this study is composed of four major parts: 1) the generation of the model data of the building; 2) the generation of indoor environmental data; 3) the creation of visualization elements; 4) data mapping. Then it realized through the generating process of visualization results.