• International conference on construction engineering and project management
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• 2015.10a
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• pp.317-320
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• 2015

Documenting work-in-progress on construction sites using images captured with smartphones, point-and-shoot cameras, and Unmanned Aerial Vehicles (UAVs) has gained significant popularity among practitioners. The spatial and temporal density of these large-scale site image collections and the availability of 4D Building Information Models (BIM) provide a unique opportunity to develop BIM-driven visual analytics that can quickly and easily detect and visualize construction progress deviations. Building on these emerging sources of information this paper presents a pipeline for model-driven visual analytics of construction progress. It particularly focuses on the following key steps: 1) capturing, transferring, and storing images; 2) BIM-driven analytics to identify performance deviations, and 3) visualizations that enable root-cause assessments on performance deviations. The information requirements, and the challenges and opportunities for improvements in data collection, plan preparations, progress deviation analysis particularly under limited visibility, and transforming identified deviations into performance metrics to enable root-cause assessments are discussed using several real world case studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.340-367
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• 2018

Storage services integration can be done for achieving high availability, improving data access performance and scalability while preventing vendor lock-in. However, multiple services environment management and interoperability have become a critical issue as a result of service architectures and communication interfaces heterogeneity. Storage federation model provides the integration of multiple heterogeneous and self-sufficient storage systems with a single control point and automated decision making about data distribution. In order to integrate diverse heterogeneous storage services into a single storage pool, we are proposing a storage service federation framework named BoxBroker. Moreover, an automated decision model based on a policy-driven data distribution algorithm and a service evaluation method is proposed enabling BoxBroker to make optimal decisions. Finally, a demonstration of our proposal capabilities is presented and discussed.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.131-143
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• 2024

Purpose - The purpose of this study was to analyze cases of big data-driven business in the financial industry, focusing on organizational structure and business processes using big data in banking industry. Design/methodology/approach - This study used a case study approach. To this end, cases of two banks implementing big data-driven business were collected and analyzed. Findings - There are two things in common between the two cases. One is that the central tasks for big data-driven business are performed by a centralized organization. The other is that the role distribution and work collaboration between the headquarters and business departments are well established. On the other hand, there are two differences between the two banks. One marketing campaign is led by the headquarters and the other marketing campaign is led by the business departments. The two banks differ in how they carry out marketing campaigns and how they carry out big data-related tasks. Research implications or Originality - When banks plan and implement big data-driven business, the common aspects of the two banks analyzed through this case study can be fully referenced when creating an organization and process. In addition, it will be necessary to create an organizational structure and work process that best fit the special situation considering the company's environment or capabilities.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.220-229
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• 2020

With the recent development of digital technology, the research paradigm is evolving towards data-driven. National management and utilization of research data is a key element not only to enhance research transparency and efficiency, but also to prepare for a data-driven society. Policies and infrastructure for sharing and utilization of research data from publicly-funded research are being actively promoted worldwide. In Korea, related regulations were recently revised to mandate to submit a data management plan (DMP) when proposing a national R&D project. In order to effectively implement the sustainable DMP system, researchers need various support. In addition, guidelines and implementation procedures are essential for management and utilization of research data at the national or institutional level. In this paper, we provide an overview of the data management plan, examine the current status and issues in Korea, and suggest a template and checklists of data management plan, and an implementation procedure at research institutes.

• Journal of Korean Academy of Nursing Administration
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• v.21 no.3
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• pp.308-316
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• 2015

Purpose: The purpose of this study was to identify the level of project perception for those nurses from research-driven hospitals and to analyze the effect of research-relevant performance in the health care field focusing on the mediated effect of research capacity and job satisfaction. Methods: Data were collected from June, 2014 to July, 2014, and participants were 106 research nurses in Research-driven hospitals. Descriptive statistics, Independent t-test, One-way ANOVA, structural equation modeling (SEM). Results: As a result, Research-relevant performance according to project perception of research nurses from Research-driven Hospitals was not statistically significant, but research capacity and job satisfaction had a mediating role. Evaluation System Perception was significantly different from Research Capacity (p<.001), Research Capacity was significantly different from Job Satisfaction (p<.001), Job Satisfaction was significantly different from Research Performance (p<.001) Conclusion: The results indicate that research capacity building and job security research nurses are able to contribute to improving research performance of research-driven hospitals.

• Informatization Policy
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• v.28 no.3
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• pp.95-111
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• 2021

To achieve a data-driven policy decision-making system, the Ministry of Strategy and Finance has formed a marketing team and is actively building upon it. This system, currently under construction, will enable data-driven financial tasks beyond simple financial administration. The U.S. has already enacted The Foundations for Evidence-Based Policymaking Act in the process of similar pursuits. Since last year, the data-driven system administrative law has been enacted in Korea, and a legal framework has been established for data-driven administrative work. The next-generation budget accounting system to fulfill its role as a data-driven system needs public policy support to operate. Innovation and transformation are needed in various areas such as data management, legal system, and installation of related systems. Accordingly, it is very timely to analyze the financial systems and policies of advanced countries such as the U.S. and U.K., which already have established and operates such a financial system. By benchmarking and applying existing financial information systems to the next-generation budget accounting system, a better system will result. In this study, major developed countries, including the U.S., U.K., France, and Canada were benchmarked and analyzed in terms of the main elements of data governance: public policy, systems, legal framework, promotion system, and service level. It was discovered that the role and direction of the national fiscal policy system that the people favor should be able to respond quickly to the recent difficult economic crisis environment such as the digital transformation trend and COVID-19.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.117-126
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• 2017

As the recent research environment and research paradigm have become data-driven, Open Science, based on openness and sharing of public research results, has emerged as a global agenda for scientific research. National policies for sharing and re-use of research data from publicly-funded research are in effect globally. Therefore, in Korea, it is urgent to build policies and infrastructure for sharing and re-use of research data. In this paper, we investigate the current status of research data management of science and technology research institutes in Korea. We conducted in-depth interviews with researchers from 22 research institutes belonging to the National Research Council of Science & Technology, and 20 universities in Korea, asking about terms of creation management utilization of research data, willingness to share data, and needs for sharing and re-use of research data. From these interviews, we drew implications for open research data and future directions.

• Journal of Aerospace System Engineering
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• v.15 no.4
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• pp.7-10
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• 2021

Including 425 Program, which is Korean military surveillance and reconnaissance satellite, there were mostly civil-driven space programs in Korea. However, there are increasing numbers of military demand-driven space program in nowadays. Furthermore, it is positive effects on launch vehicle development in Korea that the termination of Korea-U.S. missile guideline. In this paper, it emphasizes the needs of system engineering(SE) management method which meets both defense system's characteristics and space's characteristics. These characteristics are such as non-fixable after the launch, the security issue in defense system. And it also introduces SE tool, methodology and its philosophy. There are several functions that data management, issue management, risk management, and technical requirement management. Also describing its implications and direction of improvement.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.174-175
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• 2005