• 산업경영시스템학회지
• /
• 제39권2호
• /
• pp.54-63
• /
• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• 한국기록관리학회지
• /
• 제21권4호
• /
• pp.1-18
• /
• 2021

본 연구에서는 오늘날 기록관리는 정보통신 기술의 발전과 업무환경이 급변하고 정부의 규모와 여러 기능들이 확대되면서 행정업무에서 발생하는 기록과 그에 따른 데이터 생산량이 대폭 증가함에 따라 관리에 대한 중요도가 커졌다. 빅데이터의 특성을 가진 공공기록물의 개념과 빅데이터 특징을 연계하여 사례로 설명한다. 빅데이터 발생 환경에 따른 사회적, 기술적, 환경적, 경제적, 정치적 영역으로 살펴보기 위해 'STEEP'분석을 실시하였다. 공공기록관리분야에서 빅데이터 기술 적용 적절함과 필요성을 알아보고 활용이 가능한 업무 분석을 통해 공공기록관리 업무의 최우선 적용 가능한 프레임워크를 도식하고 업무 시사점을 제시하였다. 첫째, 공공기록관리 절차와 표준에 '분석' 단계를 넣고 기록관과 기록물관리전문요원들에 의해 빅데이터 분석기술을 적용할 수 있는 신규 조직과 추가연구와 시도가 필요하다. 둘째, 많은 양의 데이터 속에 비구조화 되어있고 숨겨져 있는 패턴을 발견할 수 있도록 통합적 사고와 관련이 있는 '빅데이터 분석 자격'을 갖춘 기록물관리전문요원을 양성하여야 한다. 셋째, 공공기록분야에 빅데이터기술과 인공지능을 결합하여 자가 학습 시킨 후, 맥락을 분석하고 이를 통해 공공기관의 사회 현상과 환경을 분석하고 예측 되도록 하여야 한다.

• 디지털산업정보학회논문지
• /
• 제13권2호
• /
• pp.77-85
• /
• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• 디지털산업정보학회논문지
• /
• 제12권3호
• /
• pp.1-9
• /
• 2016

The current meaning of "Big Data" refers to all the techniques for value eduction and actionable analytics as well management tools. Particularly, with the advances of wireless sensor networks, they yield diverse patterns of digital records. The records are mostly semi-structured and unstructured data which are usually beyond of capabilities of the management tools. Such data are rapidly growing due to their complex data structures. The complex type effectively supports data exchangeability and heterogeneity and that is the main reason their volumes are getting bigger in the sensor networks. However, there are many errors and problems in applications because the managing solutions for the complex data model are rarely presented in current big data environments. To solve such problems and show our differentiation, we aim to provide the solution of actionable analytics and semantic reusability in the sensor web based streaming big data with new data structure, and to empower the competitiveness.

• 지식경영연구
• /
• 제20권3호
• /
• pp.73-89
• /
• 2019

The purpose of this study is to investigate the current state of public Big Data in Seoul and suggest policy directions for the revitalization of Seoul's public Big Data. Big Data is perceived as innovation resources under the era of 4th Industrial revolution and Data economy. Especially, public Big Data serves a significant role in terms of universal access for citizens, startup, and enterprise compared with the private sector. Seoul reorganized a substructure of government's focus on Big Data and established organizations such as Big Data Campus and Urban Data Science Lab. Although the number of public open Data has increased in Seoul, there exists not much Data with characteristics similar to Big Data, such as volume, velocity, and value. In order to present the direction of Big Data policy in Seoul, we investigate the current status of Big Data Campus and Urban Data Science Lab operated by Seoul City. Considering the results of this study, we have proposed several directions that Seoul can use in establishing big data related strategies.

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

• 디지털산업정보학회논문지
• /
• 제10권1호
• /
• pp.89-97
• /
• 2014

Recently, spread of Smartphones caused activation of mobile services, because of that Big Data such as clouding service able to proceed with large amount of data which are hard to collect, save, search and analyze. Many companies collected variety of private and personal information without users' agreement for their business strategy and marketing. This situation raised social issues. As companies use Big Data, numbers of damage cases are growing. In this Thesis, when Big Data process, methods of analyze and research of data are very important. This thesis will suggest that choices of security levels and algorithms are important for security of private informations. To use Big Data, it has to encrypt the personal data to emphasize the importance of security level and selection of algorithm. Thesis will also suggest that research of utilization of Big Data and protection of private informations and making guidelines for users are require for security of private information and activation of Big Data industries.

• 한국경영과학회지
• /
• 제39권2호
• /
• pp.1-19
• /
• 2014

Recently, one of the core keywords in information technology (IT) as well as areas such as business management is big data. Big data is a term that includes technology, personnel, and organization required to gather/manage/analyze collection of data sets so large and complex that it becomes difficult to manage and analyze using traditional tools. The military has been accumulating data for a long period due to the organization's characteristic in placing emphasis on reporting and records. Considering such characteristic of the military, this study verifies the possibility of improving the performance of the military organization through use of big data and furthermore, create scientific development of operation, strategy, and support environment. For this purpose, the study organizes general status and case studies related to big data, traces back examples of data utilization by Korean's national defense sector through US military data collection and case studies, and proposes the possibility of using and applying big data in the national defense sector.

• 한국컴퓨터정보학회논문지
• /
• 제21권8호
• /
• pp.77-84
• /
• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.276-279
• /
• 2015

Along with the increase of the quantity of data in various industries, the construction industry has also developed various systems focusing on collecting data related to the construction performance such as productivity and costs achieved in construction job sites. Numerous researchers worldwide have been focusing on developing efficient methodologies to analyze such data. However, applications of such methodologies have shown serious limitations on practical applications due to lack of data and difficulty in finding appropriate analytic methodologies which were capable of implementing significant insights. With development of information technology, the new trend in analytic methodologies has been introduced and steeply developed with the new name of "big data analysis" in various fields in academia and industry. The new concept of big data can be applied for significant analysis on various formats of construction data such as structured, semi-structured, or non-structured formats. This study investigates preliminary application methods based on data collected from actual construction site. This preliminary investigation in this study expects to assess fundamental feasibility of big data analytic applications in construction.