• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2292-2313
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• 2023

With improving computing performance, various digital platforms are being developed to enable easily utilization of high-performance computing environments. EDISON 1.0 is an online simulation platform widely used in computational science and engineering education. As the research paradigm changes, the demand for developing the EDISON 1.0 platform centered on simulation into the EDISON 2.0 platform centered on data and artificial intelligence is growing. Herein, a data framework, a core module for data-centric research on EDISON 2.0 digital platform, is proposed. The proposed data framework provides the following three functions. First, it provides a data repository suitable for the data lifecycle to increase research reproducibility. Second, it provides a new data model that can integrate, manage, search, and utilize heterogeneous data to support a data-driven interdisciplinary convergence research environment. Finally, it provides an exploratory data analysis (EDA) service and data enrichment using an AI model, both developed to strengthen data reliability and maximize the efficiency and effectiveness of research endeavors. Using the EDISON 2.0 data framework, researchers can conduct interdisciplinary convergence research using heterogeneous data and easily perform data pre-processing through the web-based UI. Further, it presents the opportunity to leverage the derived data obtained through AI technology to gain insights and create new research topics.

• International Journal of Knowledge Content Development & Technology
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• v.14 no.3
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• pp.115-140
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• 2024

With the advent of the Fourth Industrial Revolution and the era of big data, the ability to handle data has become essential. This has heightened the importance and necessity of data literacy competencies. The purpose of this study is to propose a framework for data literacy competencies. To achieve this goal, data literacy frameworks from eight countries and twelve pieces of literature on data literacy competencies were analyzed and synthesized, resulting in five categories and twenty-three competencies. The five categories are: data understanding and ethics, data collection and management, data analysis and evaluation, data utilization, and data governance and systems. It is hoped that the data literacy competency framework proposed in this study will serve as a foundational resource for policies, curricula, and the enhancement of individual data literacy competencies.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.231-242
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• 2003

Multidisciplinary Design Optimization (MDO) is an optimization technique considering simultaneously multiple disciplines such as dynamics, mechanics, structural analysis, thermal and fluid analysis and electromagnetic analysis. A software system enabling multidisciplinary design optimization is called MDO framework. An MDO framework provides an integrated and automated design environment that increases product quality and reliability, and decreases design cycle time and cost. The MDO framework also works as a common collaborative workspace for design experts on multiple disciplines. In this paper, we present the architecture for an MDO framework along with the requirement analysis for the framework. The requirement analysis has been performed through interviews of design experts in industry and thus we claim that it reflects the real needs in industry. The requirements include integrated design environment, friendly user interface, highly extensible open architecture, distributed design environment, application program interface, and efficient data management to handle massive design data. The resultant MDO framework is datasever-oriented and designed around a centralized data server for extensible and effective data exchange in a distributed design environment among multiple design tools and software.

• Journal of Information Technology Applications and Management
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• v.10 no.4
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• pp.103-118
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• 2003

This study presents a database quality evaluation framework. As a way to build a framework, this study expands data quality management to include data transformation processes as well as data. Further, an information structure graph is applied to represent data transformations processes. An information structure graph is absed on a relational database scheme. Thus, data transformation processes may be stored in a relational database. This kind of integration of data transformation metadata with technical metadata eases evaluation of database qualities and their causes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.361-366
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• 2004

Geographic Information has been used widely for landuse and management, city plan, and environment and disaster management, etc., But geographic information has been built for individual cases using various methods. Therefore, the discordancy in data, double investment, confusion of use and difficulty of decision supporting system have been occurred. In order to solve these problems, national government is need to framework database. This framework database was enacted for building and use of National Geographic Information System and focused on basic plan of the second national geographic information system. Also, the framework database was selected of eight fields by NGIS laws and 19 detailed items through meeting of framework committee since 2002. In this research, The 19 detailed items( road, railroad, coastline, surveying control point etc.,) of framework database consider a Priority order, In the result of this research, the framework database is obtain to a priority order for building and the national government will carry effectively out a budget for the framework database building. Each of 19 detailed items is grouping into using the priority order of the framework database by AHP analysis method and verified items by decision tree analysis method. The one of the highest priority order items is a road, which is important for building, continuous renovation, and maintain management for use.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.159-166
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• 2019

The collection and manipulation of Internet of Things (IoT) data is increasing at a fast pace and its importance is recognized in every sector of our society. For efficient utilization of IoT data, the vast and varied IoT data needs to be reliable and meaningful. In this paper, we propose an IoT framework to realize this need. The IoT framework is based on a four layer IoT architecture onto which context aware computing technology is applied. If the collected IoT data is unreliable it cannot be used for its intended purpose and the whole service using the data must be abandoned. In this paper, we include techniques to remove uncertainty in the early stage of IoT data capture and collection resulting in reliable data. Since the data coming out of the various IoT devices have different formats, it is important to convert them into a standard format before further processing, We propose the RDF format to be the standard format for all IoT data. In addition, it is not feasible to process all captured Iot data from the sensor devices. In order to decide which data to process and understand, we propose to use contexts and reasoning based on these contexts. For reasoning, we propose to use standard AI and statistical techniques. We also propose an experiment environment that can be used to develop an IoT application to realize the IoT framework.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.293-301
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• 2002

MGF(Marine Geographical Framework) data are the essential data sets concerning graphical and attribute information on coast and ocean among various marine-related data, which consist of framework data of the National Spatial Data Infrastructure(NSDI). This study did research and analyzed the development of current data, the situation of its usage, related technical environment and case study of foreign countries through the survey on the users and experts. Then the item of marine geographical framework data was selected in accordance with the measures for usage and management of possible MGF data. A map was pilot producted based on selected items and MGF data was presented through making up some problems shown ill the process. The importance of GIS will be growing continuously which can develop, deal with and provide the various data to efficiently manage coast and ocean. Accordingly, the MGF data will be applied to various areas such as Internet or raw data for marine information system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.223-228
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• 2015

Korean climate becoming increasingly subtropical by climate warming makes local heavy rainfall frequently. To avoid damages from the local heavy rainfall, we need a forecasting service for a great number of clients. However, there is not the framework for the service based on wireless data broadcasting yet. In this paper, we design and implement a service framework for local heavy rainfall forecasting using wireless data broadcast. The developed service framework has scalability that can adopt various data scheduling and indexing schemes. We show the efficiency of the proposed framework to forecast local heavy rainfall through a simulation study.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.107-113
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• 2016

In this paper, by managing the biometric data is changed with the passage of time, a systematic and scientifically propose a framework to increase the bio-vector generation efficiency of the smart health care. Increasing the development of human life as a medicine and has emerged smart health care according to this. Organic and efficient health management becomes possible to generate a vector when the biological domain to the wireless communication infrastructure based on the measurement of the health status and to take action in accordance with the change of the physical condition. In this paper, we propose a framework to create a bio-vector that contains information about the current state of health of the person. In the proposed framework, Bio vectors may be generated by collecting the biometric data such as blood pressure, pulse, body weight. Biometric data is the raw data from the bio-vector. The scope of the primary data can be set to active. As the collecting biometric data from multiple items of the bio-recognition vectors may increase. The resulting bio-vector is used as a measure to determine the current health of the person. Bio-vector generating the proposed framework, it can aid in the efficiency and systemic health of healthcare for the individual.