• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.57-68
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• 2017

The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.399-408
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• 2015

This paper presented airquality data through data visualization in several ways and described its characteristics related to statistical methods for analysis. Software R was used for visualization tools. The airquality data was measured in New York city from May to September of year 1973. First, simple, exploratory data analysis was done in terms of both data visualization and analysis to find out univariate characteristics. Then through data transformation and multiple regression analysis, model for describing the airquality level was found. Also, after some data categorization, overall feature of the data was explored using box plot and three-dimensional perspective drawing and scatter plot.

• Journal of Information Technology Services
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• v.7 no.1
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• pp.205-218
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• 2008

This paper proposes a geospatial data visualization system supporting validation of GML documents. GIS systems manage and use both of spatial and non-spatial data. Currently, most GIS systems represent spatial data in GML (Geography Markup Language) developed by OGC. GML is a language for representation and sharing of spatial information, and until now many systems have been developed in GML. GML does not support expression of non-spatial data, i.e., relational information of spatial objects, and thus most systems extend GML to describe non-spatial information. However, it causes an issue that the systems only accepting standard GML documents cannot process the extended documents. In this paper, we propose a new GIS data visualization system to resolve the aforementioned Issue. Our proposed system allows the representation of both types of data supporting independency of spatial data and non-spatial data. It enhances interoperability with other relevant systems. Therefore, we can develop a rich and high Quality geospatial information services.

• Journal of Information Technology Services
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• v.6 no.1
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• pp.127-140
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• 2007

Due to the development of information technologies and new businesses related to moving objects, the need for the storage and analysis of moving object data is increasing rapidly. Moving object data have a spatiotemporal nature which is different from typical business data. Therefore, different methods of data storage and analysis are required. This paper proposes a multidimensional data model and data visualization to analyze moving object data efficiently and effectively. We expect that decision makers can understand the movement pattern of moving objects more intuitively through the proposed implementation.

• Genomics & Informatics
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• v.12 no.1
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• pp.21-34
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• 2014

A visual analysis approach and the developed supporting technology provide a comprehensive solution for analyzing large and complex integrated genomic and biomedical data. This paper presents a methodology that is implemented as an interactive visual analysis technology for extracting knowledge from complex genetic and clinical data and then visualizing it in a meaningful and interpretable way. By synergizing the domain knowledge into development and analysis processes, we have developed a comprehensive tool that supports a seamless patient-to-patient analysis, from an overview of the patient population in the similarity space to the detailed views of genes. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, and gene comparison. We demonstrate our approach with medical scientists on a case study of childhood cancer patients on how they use the tool to confirm existing hypotheses and to discover new scientific insights.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.227-234
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• 2002

This study was conducted to nondestructively estimate the volumetric information of peach and pit and to visualize the 3D information of internal structure from magnetic resonance imaging(MRI) data. Bruker Biospec 7T spectrometer operating at a proton reosonant frequency of 300 MHz was used for acquisition of MRI data of peach. Image processing algorithms and visualization techniques were implemented by using MATLAB (Mathworks) and Visualization Toolkit(Kitware), respectively. Thresholding algorithm and Kohonen's self organizing map(SOM) were applied to MRI data fur region segmentation. Volumetric information were estimated from segemented images and compared to the actual measurements. The average prediction errors of peach and pit volumes were 4.5%, 26.1%, respectively for the thresholding algorithm. and were 2.1%, 19.9%. respectively for the SOM. Although we couldn't get the statistically meaningful results with the limited number of samples, the average prediction errors were lower when the region segmentation was done by SOM rather than thresholding. The 3D visualization techniques such as isosurface construction and volume rendering were successfully implemented, by which we could nondestructively obtain the useful information of internal structures of peach.

• International Journal of Contents
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• v.15 no.4
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• pp.1-7
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• 2019

As the recent developments of artificial intelligence, particularly machine-learning, impact every aspect of society, they are also increasingly influencing creative fields manifested as new artistic tools and inspirational sources. However, as more artists integrate the technology into their creative works, the issues of diversity and fairness are also emerging in the AI-based creative practice. The data dependency of machine-learning algorithms can amplify the social injustice existing in the real world. In this paper, we present an interactive visualization system for raising the awareness of the diversity and fairness issues. Rather than resorting to education, campaign, or laws on those issues, we have developed a web & ML-based interactive data visualization system. By providing the interactive visual experience on the issues in interesting ways as the form of web content which anyone can access from anywhere, we strive to raise the public awareness of the issues and alleviate the important ethical problems. In this paper, we present the process of developing the ML-based interactive visualization system and discuss the results of this project. The proposed approach can be applied to other areas requiring attention to the issues.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.421-428
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• 2009

On the visualization of categorical data, if the number of categories is small, we can consider Hayashi Quantification Method 3 for visualization of the categories of the variables. But it is known that the method is unstable because it quantifies more significantly for the small frequency categories rather than large frequency categories. The purpose of this research is to propose the visualization of large two-way crosstabulation data by PLS methods for checking the relationship between the categories of row and column variables. In this research, we utilize the PLS visualization methods (Huh et al., 2007) that is proposed for visualization of the qualitative data to visualize the categories of the large categorical data. We also compared both methods by applying them to real data, and studied the results from PLS visualization method on the real categorized data with many categories.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.79-86
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• 2005

The Qis visualizational spreadsheet environment is shown to be extremely effective in supporting the organized visualization of multi-dimensional data sets. The Qis consists of the reconfigurative 2D arrangement of spreadsheet elements at run time and each spreadsheet element has a novel framestack. As the feature, it supports 3D data structure of each element on the Qis. It enables the visualization spreadsheet to effectively manage, rapidly organize, and compactly encapsulate multi-dimensional data sets for visualization. Using several experiments with scientific users, the Qis has been demonstrated to be a highly interactive visual browsing tool for the analysis of multidimensional data, displaying 2D and 3D graphics, and rendering in each frame of the spreadsheet.

• Journal of Electrical Engineering and Technology
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• v.1 no.3
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• pp.287-294
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• 2006

Recently, switchboards for MV/LV distribution customers have been united and digitalized rapidly. This paper proposes the effective information visualization method for the data measured from cubicle switchboards for MV/LV distribution customers. We developed the algorithm that analyzes abundant data measured by switchboards and displays them to overall users, such as fire information index, power condition index, switchboard safety index, and power diminution index. Using a touch screen made users to operate it easily. User interface was also improved by taking graphic visualization. We guess the information visualization method suggested in this paper shows the new direction that heavy electrical equipments including switchboards are going to develop in the future.