• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.77-86
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• 2022

The destructive impact of contagious diseases outbreaks on all life facets necessitates developing effective solutions to control these diseases outbreaks. This research proposes an end-to-end, data-driven platform which consists of multiple modules that are working in harmony to achieve a concrete goal: early detection of contagious diseases outbreaks (i.e., epidemic diseases detection). Achieving that goal enables decision makers and people in power to act promptly, resulting in robust prevention management of contagious diseases. It must be clear that the goal of this proposed platform is not to predict or forecast the spread of contagious diseases, rather, its goal is to promptly detect contagious diseases outbreaks as they happen. The front end of the proposed platform is a web-based dashboard that visualizes diseases outbreaks in real-time on a real map. These outbreaks are detected via another component of the platform which utilizes data mining techniques and algorithms on gathered datasets. Those gathered datasets are managed by yet another component. Specifically, a mobile application will be the main source of data to the platform. Being a vital component of the platform, the datasets are managed by a DBMS that is specifically tailored for this platform. Preliminary results are presented to showcase the performance of a prototype of the proposed platform.

• Journal of Information Science Theory and Practice
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• 제8권2호
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• pp.68-78
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• 2020

This study is a preliminary study to develop an evaluation framework necessary for evaluating the DataON platform. The first objective is to examine expert perceptions of the level of DataON platform construction. The second objective is to evaluate the importance, stability, and usability of DataON platform features over OpenAIRE features. The third objective is to derive weights from the evaluation perspective for future DataON platform evaluation. The fourth objective is to examine the preferences of experts in each evaluation perspective and to derive unbiased evaluation criteria. This study used a survey method for potential stakeholders of the DataON platform. The survey included 12 professionals with at least 10 years of experience in the field. The 57 overall functions and services were measured at 3.1 out of 5 for importance. Stability was -0.07 point and usability was measured as -0.05 point. The 42 features and services scored 3.04 points in importance. Stability was -0.58 points and usability was -0.51 points. In particular, the stability and usability scores of the 42 functions and services provided as of 2018 were higher than the total functions were, which is attributed to the stable and user-friendly improvement after development. In terms of the weight of the evaluation point, the collection quality has the highest weight of 27%. Interface usability is then weighted 22%. Subsequently, service quality is weighted 19%, and finally system performance efficiency and user feedback solicitation are equally weighted 16%.

• Journal of Advanced Research in Ocean Engineering
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• 제3권1호
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• pp.32-40
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• 2017

Recently, the amount of data to be processed and the complexity thereof have been increasing due to the development of information and communication technology, and industry's interest in such big data is increasing day by day. In the shipbuilding and offshore industry also, there is growing interest in the effective utilization of data, since various and vast amounts of data are being generated in the process of design, production, and operation. In order to effectively utilize big data in the shipbuilding and offshore industry, it is necessary to store and process large amounts of data. In this study, it was considered efficient to apply Hadoop and R, which are mostly used in big data related research. Hadoop is a framework for storing and processing big data. It provides the Hadoop Distributed File System (HDFS) for storing big data, and the MapReduce function for processing. Meanwhile, R provides various data analysis techniques through the language and environment for statistical calculation and graphics. While Hadoop makes it is easy to handle big data, it is difficult to finely process data; and although R has advanced analysis capability, it is difficult to use to process large data. This study proposes a big data platform based on Hadoop for applications in the shipbuilding and offshore industry. The proposed platform includes the existing data of the shipyard, and makes it possible to manage and process the data. To check the applicability of the platform, it is applied to estimate the weights of offshore structure topsides. In this study, we store data of existing FPSOs in Hadoop-based Hortonworks Data Platform (HDP), and perform regression analysis using RHadoop. We evaluate the effectiveness of large data processing by RHadoop by comparing the results of regression analysis and the processing time, with the results of using the conventional weight estimation program.

• 산업경영시스템학회지
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• 제40권2호
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• pp.68-77
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• 2017

In order to implement the smart home environment, we need an intelligence service platform that learns the user's life style and behavioral patterns, and recommends appropriate services to the user. The intelligence service platform should embed a couple of effective and efficient data mining algorithms for learning from the data that is gathered from the smart home environment. In this study, we evaluate the suitability of data mining algorithms for smart home intelligent service platforms. In order to do this, we first develop an intelligent service scenario for smart home environment, which is utilized to derive functional and technical requirements for data mining algorithms that is equipped in the smart home intelligent service platform. We then evaluate the suitability of several data mining algorithms by employing the analytic hierarchy process technique. Applying the analytical hierarchy process technique, we first score the importance of functional and technical requirements through a hierarchical structure of pairwise comparisons made by experts, and then assess the suitability of data mining algorithms for each functional and technical requirements. There are several studies for smart home service and platforms, but most of the study have focused on a certain smart home service or a certain service platform implementation. In this study, we focus on the general requirements and suitability of data mining algorithms themselves that are equipped in smart home intelligent service platform. As a result, we provide a general guideline to choose appropriate data mining techniques when building a smart home intelligent service platform.

• 한국빅데이터학회지
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• 제4권2호
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• pp.93-103
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• 2019

본 논문에서는 수산과학 R&D 정보의 빅데이터 플랫폼 구축과 메타 데이터 관리기법에 관해 소개한다. 빅데이터 플랫폼에서는 다양한 유형의 수산과학 R&D 정보를 수집하여 통합 연계하고, 이를 데이터 레이크 형태로 구축하는 방안을 제시한다. 수산과학 분야에서 수집, 축적되고 있는 기존의 데이터와 함께 위성영상 데이터, 연구보고서 등 비정형 빅데이터까지 수집하여 다양한 분석을 지원하는 빅데이터 플랫폼의 구축방안을 제시한다. 다음으로 데이터 추출과 전처리 및 저장 과정에서 메타 데이터를 수집하고 관리함으로써 수산과학 빅데이터의 체계적인 관리가 가능하도록 한다. 빅데이터 플랫폼 구축과 함께 메타 데이터를 표준양식으로 구축함으로써 데이터의 수집, 저장, 활용 및 유통 등 데이터 수명주기 전반에 걸쳐 체계적이고도 지속적인 빅데이터 관리 방안을 제시하는데 의의가 있다.

• 인터넷정보학회논문지
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• 제19권1호
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• pp.123-130
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• 2018

With the emergence of a new paradigm called Open Science and Big Data, the need for data sharing and collaboration is also emerging in the computational science field. This paper, we analyzed data-driven research cases for computational science by field; material design, bioinformatics, high energy physics. We also studied the characteristics of the computational science data and the data management issues. To manage computational science data effectively it is required to have data quality management, increased data reliability, flexibility to support a variety of data types, and tools for analysis and linkage to the computing infrastructure. In addition, we analyzed trends of platform technology for efficient sharing and management of computational science data. The main contribution of this paper is to review the various computational science data repositories and related platform technologies to analyze the characteristics of computational science data and the problems of data management, and to present design considerations for building a future computational science data platform.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.34-34
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• 2022

Capacity building for bioinformatics could be achieved with the systematic training of research staff and higher degree students in the current best practices for analysis of data from 'omic-type experiments. It is anticipated that the KOICA-University of the Philippines Los Baños - International Rice Research Insitute Agricultural Genomics Research Center activities will focus on the use of next generation sequencing technology for genome sequencing and annotation, genome variant discovery for use in GWAS and QTL mapping, and transcriptome analysis of organisms important to agriculture and food security. Such activities require that researchers have high levels of knowledge and skills in bioinformatics in order to gain insights from the results of the experiments performed. In this talk the bioinformatic tools/solutions and online training materials already available will be presented, as well the upcoming resources under development in support of the project.

• 한국CDE학회논문집
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• 제21권3호
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• pp.334-340
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• 2016

As Information Technology (IT) is developed constantly, big data is becoming important in various industries, including ship and offshore industry where a lot of data are being generated. However, it is difficult to apply big data to ship and offshore industry because there is no generalized platform for its application. Therefore, this study presents a big data platform based on the Hadoop for applications in ship and offshore industry. The Hadoop is one of the most popular big data technologies. The presented platform includes existing data of shipyard and is possible to manage and process the data. To check the applicability of the platform, it is applied to estimate the weight of offshore plant topsides. The result shows that the platform can be one of alternatives to use effectively big data in ship and offshore industry.

• 한국IT서비스학회지
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• 제21권5호
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• pp.15-28
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• 2022

Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.

• Spatial Information Research
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• 제20권6호
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• pp.99-107
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• 2012

최근 건설데이터를 활용하는 BIM과 공간데이터를 활용하는 GIS 간의 통합 및 연계를 시도하려는 연구가 많이 이루어지고 있다. 하지만, BIM과 GIS의 데이터모델이 서로 너무 다른 특징을 가지고 있어 두 데이터모델 간의 통합을 통한 상호운용은 매우 어려운 실정이다. 따라서 본 연구에서는 BIM과 GIS의 효율적인 상호운용성을 시스템적으로 확보하기 위한 BIM과 GIS 상호운용 플랫폼을 설계하여 제시한다. 그리고 기존의 상용 소프트웨어들을 분석하여 본 연구에서 제안한 플랫폼에 필요한 요소기술과 기능들을 정의하여 제시한다.