빅데이터를 기반으로 한 경관디자인 국내 학위 연구 동향 분석

박혜경,이재호 한국공간디자인학회 2023 한국공간디자인학회논문집 Vol.18 No.7

(Background and Purpose) Research based on big data is being actively conducted in various fields such as cities, architecture, landscapes, and design. The scope of use of big data is gradually expanding, and the number of cases using big data is steadily increasing in the landscape design field, but trend analysis or trend research related to this is still insufficient. Therefore, this study aims to identify the types and analysis techniques of big data used according to the research characteristics and targets in the landscape design field by conducting a survey and trend analysis of studies using big data. Through this, the characteristics of big data analysis techniques that are highly utilized by type and field/target of research can be incorporated into the landscape design process, or it is intended to be a foundation study that can contribute to the insights or follow-up research necessary for the proposal of new research. (Method) This study conducted the first and second surveys that limit the categories to be investigated, targeting domestic master's and doctoral dissertations related to design using big data. In the first survey, seven words (design, landscape, city, architecture, product, vision, design + landscape) related to big data and design were combined to search for papers, and three words related to the main perspective of this study (city, landscape, design) were narrowed down, and the research fields of these studies and applied big data analysis techniques were identified. In the second survey, "methodology" and "process" were added and recombined into the subject word to extract research used in design based on the first survey. In this process, a total of 47 papers were identified, the final four were selected and the research contents were analyzed. (Results) The surveys confirmed that the interest and utilization of research using big data are continuously increasing in all areas of "landscape", "design", and "city". Text mining techniques were being used as the most basic method for big data analysis, and it was confirmed that certain phenomena were analyzed from various angles by using text mining in parallel or additional separate techniques depending on the subject. (Conclusions) Research in the field of landscape design using big data analysis techniques is expected to continue in the future. In particular, in the landscape design-related fields, the use of opinion mining (emotional analysis) was on the rise to solve user-centered problems, and need to revitalize various research that can discover new formativeness and aesthetics through emotion. In addition, if guidelines and processes are developed by applying and combining various big data techniques, the level of related fields is expected to increase, such as minimizing errors in carrying out certain tasks and securing quality above a certain level.

중국 빅데이터 거래에 관한 법적 고찰 -정보법을 중심으로-

김군 ( Jin Jun ) 중앙대학교 법학연구원 문화미디어엔터테인먼트법연구소 2018 문화.미디어.엔터테인먼트 법 Vol.12 No.2

The integration of information technology and economic society promotes the rapid development of Big Data. According to the survey conducted by the China Academy of Information and Communications Technology that the size of China's Big Data industry was 470 billion RMB in 2017, demonstrating a 30% year-on-year increase. There can be no doubt that Big Data industry is becoming a new economic growth engine and will play significant role for the future patterns of the information industry. Although Big Data transactions have developed vigorously, there is still no specific rules to regulate it. In practice, Big Data transaction is regulated by The General Rules of the Civil Law, Contact Law, Copyright Law, Law of the PRC against Unfair Competition, and the Information Protection of related regulations and policies. In order to provide grounds for Big Data transactions, this article introduces the general situation of China's Big Data Exchanges and the types of Big Data transactions, as well as the laws related to Big Data and the trading rules of Big Date Exchanges in China. In fact, there is no explicit rules for attribution of big data, and the attribution of Big Data is determined by agreement in legal practice generally. If there is no agreement in previous, the right of Big Data should be attributed to the Data collector (or creator). In the aspect of Big Data circulations, the information collector, which shall specify the using of information method, the extent and purpose of information to the individuals, shall obtain the individuals consent in advance. Finally, this article also review two cases related Big Data. According to the ruling, without permission of using Data, which is legally collected by others, is an unfair competition. In the case of cookies, the court established a standard for using personal information to infringe on the privacy rights of individuals.

A Study on Open API of Securities and Investment Companies in Korea for Activating Big Data

Gui Yeol Ryu 한국인터넷방송통신학회 2019 Journal of Advanced Smart Convergence Vol.8 No.2

Big data was associated with three key concepts, volume, variety, and velocity. Securities and investment services produce and store a large data of text/numbers. They have also the most data per company on the average in the US. Gartner found that the demand for big data in finance was 25%, which was the highest. Therefore securities and investment companies produce the largest data such as text/numbers, and have the highest demand. And insurance companies and credit card companies are using big data more actively than banking companies in Korea. Researches on the use of big data in securities and investment companies have been found to be insignificant. We surveyed 22 major securities and investment companies in Korea for activating big data. We can see they actively use AI for investment recommend. As for big data of securities and investment companies, we studied open API. Of the major 22 securities and investment companies, only six securities and investment companies are offering open APIs. The user OS is 100% Windows, and the language used is mainly VB, C#, MFC, and Excel provided by Windows. There is a difficulty in real-time analysis and decision making since developers cannot receive data directly using Hadoop, the big data platform. Development manuals are mainly provided on the Web, and only three companies provide as files. The development documentation for the file format is more convenient than web type. In order to activate big data in the securities and investment fields, we found that they should support Linux, and Java, Python, easy-to-view development manuals, videos such as YouTube.

증거기반정책에서 빅데이터 활용에 관한 연구

김길수 한국비교정부학회 2024 한국비교정부학보 Vol.28 No.3

(Purpose) It can be said that data-driven innovation is necessary to improve efficiency and effectiveness by establishing policies based on big data and to provide public services tailored to citizens’ administrative needs. This study aims to explore how evidence-based policies can be optimized with big data, using the policy process as a general model. (methodology/approach) Based on the previous research, this study divided the policy process into interrelated stages of policy agenda setting, policy making, policy implementation, and policy evaluation and examined how big data is utilized in each stage through a research methodology called literature review which collects and systematically analyzes literature related to achieving the research goal. Based on this, implications for how big data can optimize the policy process were derived. (Findings/ Research implications) This study understands evidence-based policy as a systematic approach that can provide the best evidence to the policy process, and examines how big data can be utilized by dividing the policy process into policy agenda setting, policy making, policy implementation, and policy evaluation. It was confirmed that big data is most actively utilized in the policy agenda setting process. Big data can help develop policy alternatives and predict the results that may occur when they are applied, and in the implementation stage, it can provide immediate feedback on the success or failure of the policy and data generation. Evaluation can be conducted at all stages of the policy, providing the necessary evidence for the policy in real time. The perspective on utilizing big data in the public policy field seems to be based on technological optimism. In other words, it is thought that there is more data, better information can be derived, and this will promote better decisions. Therefore, it seems that they are focusing on developing techniques to derive insights from big data. However, can better information simply lead to better decisions? Decisions are the subject of politics. Politics determines values. Who prioritizes what values, what is included and excluded, and how data is collected, analyzed, and interpreted can be said to be the realm of politics. Therefore, utilizing big data in the policy domain must simultaneously consider the technical aspect and the value determination or political aspect.

빅데이터를 활용한 사회과 교수·학습 모형의 탐색

황홍섭 한국사회과교육연구학회 2019 사회과교육 Vol.58 No.1

제4차 산업혁명은 빅데이터와 인공지능을 핵심으로 지능정보사회를 지향하고 있다. 이에 따라 우리의 삶과 교육 전반에 패러다임 전환을 요구하고 있다. 이에 본 연구의 목적은 빅데이터를 활용하여 사회과 교수·학습 모형을 탐색하는 것이다. 연구 목적을 달성하기 위해, 첫째 목표는 모형을 탐색하기에 앞서 현재 및 미래 사회의 모습인 복잡계 및 초복잡계를 검토하여 빅데이터 활용교육의 의의를 논의하였다. 둘째 목표는 빅데이터 활용 사회과 교수·학습 모형을 빅데이터, 교수·학습 및 미래교육에 대한 단어 검색 결과와 문헌연구를 바탕으로 탐색한다. 셋째 목표는 빅데이터 활용 사회과 교수·학습 모형을 적용한 수업사례를 개발하였다. 본 연구를 위한 빅데이터 검색어는 빅데이터, 사회과 교수·학습, 미래교육으로 하였고, 분석 대상은 3개의 포털 사이트(네이버, 다음, 구글)와 SNS(트위터, 페이스북), 그리고 RISS의 국내학술지논문 및 학위논문으로 하였다. 분석 기법으로 텍스트 마이닝(text mining)을 비롯한 워드클라우드 분석(wordcloud analysis)과 네트워크 분석(network analysis)을 활용하였다. 연구결과는 다음과 같다. 첫째, 4차 산업혁명으로 인한 사회는 복잡계 및 초복잡계 현상이 가속화되고 있으며, 빅데이터는 이러한 복잡계 및 초복잡계 현상을 잘 담아내고 있다. 이러한 빅데이터는 사회과 교육에 있어서 시대에 맞는 정보원, 자료, 도구, 수단, 멘토, 조력자, 협력자등 다양하게 표현되며, 이것을 사회과 교육에 적극적으로 활용할 필요성이 있다. 둘째, 빅데이터를 활용한 교수·학습 모형은 빅데이터가 복잡계 및 초복잡계의 특성을 잘 반영하고 있기 때문에 현재 및 미래사회의 문제 해결을 통해 학습자의 가치를 창출하여 최적화된 행동을 할 수 있도록 해 주는 문제해결학습 모형이 적절하다. 특히 빅데이터를 활용한 교수·학습 모형은 복잡한 문제를 전수조사에 가까운 데이터를 마이닝(mining)하면서 문제를 단순화해가면서 해결해가는 귀납적 절차에 의한 자기 주도의 연역적 학습이 가능하다. 셋째, 빅데이터 를 활용한 사회과 교수·학습 활용 사례는 현장에서 빅데이터를 어떻게 활용하여 수업을 할 것인가에 대한 방향성을 제시해 줄 것이다. 결론적으로 빅데이터를 활용한 사회과 교수·학습 모형은 복잡계(complex system) 및 초복잡계(supercomplex system) 현상으로 나타나는 현재 및 미래사회에서 창의적 문제 해결을 위한 적절한 모형으로 2015개정 교육과정에서 요구하는 사회과 핵심역량을 구현하기에 유용하다. 빅데이터를 활용한 교수·학습 모형은 협력과 개인화(personalization) 전략을 통해 학습자 맞춤형 수업을 지원하여 창의 융복합 인재 양성에 기여할 것으로 기대된다. The fourth industrial revolution is aiming at intelligence information society with the big data and artificial intelligence. As a result, we are demanding a paradigm shift. The purpose of this study is to explore social studies teaching and learning models using big data. In order to achieve the purpose of the research, the first goal is to examine the significance of the big data utilization education by examining the complexity and the supercomplexity which is the present and future society before exploring the model. The second goal is to explore the social studies teaching and learning model of big data utilization based on the word search results and the research on big data, teaching and learning, and future education. The third goal is to develop a case study using the social studies teaching and learning model of big data utilization. The search words for this study were “big data”, “social studies teaching and learning”, and “future education”. The subjects of analysis were three portal sites(Naver, Daum, Google), SNS(Twitter, Facebook), RISS(Research Information Sharing Service). The results of the study are as follows. First, the society caused by the fourth industrial revolution is accelerating the complexity and supercomplexity phenomenon, and big data is well - suited to this complexity and supercomplexity phenomenon. These big data are represented in various ways such as information sources, materials, tools, means,analysis and evaluation tools, mentors, helpers, and cooperators in social studies education, and it is necessary to actively utilize them in social studies education. Second, the teaching and learning model using big data reflects the characteristics of the complex system and the complexity of the big data. Therefore, it can create the value of the learners through solving the problems of the present and future society, The problem-solving learning model is appropriate. In particular, teaching and learning models using big data can lead to self-directed deductive learning through inductive procedures that solve complex problems by mining data close to the whole survey while simplifying the problems. Third, social studies teaching and learning using big data will give directions on how to use big data in the field.In conclusion, the social studies teaching and learning model using big data is an appropriate model for solving creative problems in present and future societies that appear as complex system and supercomplex system phenomenon. It is useful for implementing competencies. The teaching and learning model using big data is expected to contribute to the cultivation of creative talents by supporting learner customized class through cooperation and personalization strategy.

빅데이터 환경의 도래와 개인정보 보호방안

김용훈(Kim Yong Hoon) 경희법학연구소 2018 경희법학 Vol.53 No.1

정보화시대는 그 면모를 급속도록 변형시키고 있듯이 우리의 생활에서 정보의 중요성은 아무리 강조해도 과언이 아니다. 이와 같은 상황은 인터넷에 힘입은 바 큰데 실제적으로 인터넷 상의 정보량은 현재 천문학적인 규모에 이르고 있어서 우리는 정보의 홍수에 살고 있다는 평가가 어색하지 않다. 그런데 이와 같은 현상을 보다 강화하는 기제가 등장하였으니 그것은 빅데이터이다. 빅데이터란 “기존 데이터 수집·저장·관리·분석의 역량을 넘어서는 대량의 정형 또는 비정형 데이터 세트 및 이러한 데이터로부터 가치를 추출하고 결과를 분석하는 기술”을 일컫는 것으로 이를 통하여 사고와 재난의 예측과 효과적인 예방 나아가 범죄에 대한 효과적인 대응을 가능하도록 한다는 점에서 이의 중요성과 의의는 무시할 수 없게 된 것이 사실이다. 하지만 이로 말미암아 개별적인 사익 특히 프라이버시권 등 일정한 기본권과의 상충 상황이 가능해졌다는 점에서 당해 빅데이터의 활용 필요성만을 강조할 수는 없게 되었다. 실제적으로 빅데이터의 활용은 일정 정도의 개인 정보를 활용하는 것은 전제로 하기 때문이다. 결국 이는 빅데이터 활용이라는 공익과 프라이버시권이라는 사익의 상충 상황을 의미하는 것이기 때문에 일관적이고 효과적인 빅데이터의 활용을 담보하기 위해서는 양 이익간 형량 작업이 필요하다고 보아야 한다. 당해 작업을 위하여 본격적인 규범을 도입한 실체가 있는 데 유럽연합이다. 유럽연합은 기존의 정보보호지침에서 정보보호규칙(General Data Protection Regulation: GDPR)이라는 규칙을 제정하여 빅데이터 시대에 임하여 보다 적극적인 입장을 고수하고 있는 것이다. 우리 역시 향후 빅데이터의 활용 필요성과 가능성을 무시할 수 없다는 점에서 이에 대한 대비가 필요하다고 할 수 있다. 유럽연합의 경험을 참고하여 시사하는 바를 확보할 수 있을 것인데 프로파일링 거부권, 익명화 조치, 프라이버시 바이 디자인 그리고 동의 요건의 강화 등의 도입을 적극적으로 고려할 수 있을 것이다. We can not emphasize the importance of information in our life too much as information age changes itself rapidly. Because this situation was brought about by the internet, we can evaluate that we are living the flood of information substantially. By the way it is true that Big Data is strengthening such a phenomena. Big Data is to be defined as “a technology to extract the value from bulk of regular or irregular Data Set and to analyze the result beyond the past capacity of collection·storage·management·analysis of Data”. It is reasonable to say that the Big Data is important to some extent due to the fact that we can predict the accident and disaster and prevent and take action against the crimes in an effective way. However we need to be concerned about the possibility that the availability and the usage of Big Data may lead to the invasion of individual privacy right particularly the Personal Information Control Right. Thus we are not able to emphasize the necessity and possibility of the Big Data usage. Practically speaking, it is not unreasonable to postulate that the usage of Big Data presuppose the utilization of individual information. In the long run, since this situation means that there is confliction between the interest of usage of Big Data(public interest) and the interest of individual information(private interest), it is essential to balance between both interests for the sake of effective utilization of Big Data. We need to pay attention to the fact that there is an entity to adopt the legal instrument in order to balance between both interests, European Union. In other words, European Union has a strong stand on the regulation of Big Data by enactment of new legal instrument such as General Data Protection Regulation holding a higher legal position than Data Protection Directive in European Union legal order. It is true that we should prepare the efficient usage of Big Data in that there is necessity and possibility of availability of Big Data in our society. Therefore we can get by and secure various legal means for the sake of effective usage of Big Data by referring to the experience of European Union such ad the right of profiling denial, anonymisation action, Privacy Design and the strengthening of agreement conditions etc.

빅데이터 도입의도에 미치는 영향요인에 관한 연구: 전략적 가치인식과 TOE(Technology Organizational Environment) Framework을 중심으로

가회광,김진수 한국경영정보학회 2014 Asia Pacific Journal of Information Systems Vol.24 No.4

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which...

미국 대통령선거와 정치빅데이터 유용성 분석

동성혜 미국헌법학회 2019 美國憲法硏究 Vol.30 No.2

본 논문은 정치빅데이터의 유용성을 정치적 커뮤니케이션의 본질 가운데 선거전략과 여론형성 및 분석이라는 정치과정 차원에 초점을 맞추었다. 이를 중심으로 2012년 미국 대통령선거 당시 오바마 캠프가 정치빅데이터를 활용한 내용을 분석하였다. 제4차 산업혁명시대의 핵심 기술인 빅데이터는 사회변화와 기술혁신의 연결고리로 인간과 사회, 자연과 사물에 기술을 접목시켜 만들어낸 ‘초연결성 네트워크’의 모든 정보들의 집합체이다. 이러한 방대한 양의 빅데이터는 존재 자체가 갖는 의미보다는 수집과 분석, 공유를 통하여 무엇을 분석하고 어떻게 해석하느냐에 대한 ‘통찰’이 전제되어야 미래를 예측할 수 있다. 정치 영역에서의 빅데이터도 마찬가지다. IT기술의 발전과 확산은 정당, 정치인, 유권자 모두의 정치적 인식과 행위에 영향을 줌으로써 정치과정의 패러다임을 변화시키고 있다. 정치 영역에서의 빅데이터에 대한 접근은 ‘인간에 대한 정보’와 ‘상호작용’이라는 점에서 정치적 커뮤니케이션 차원에서 바라보았고, 정치빅데이터 활용을 정치권력의 획득과 유지를 위한 정치활동으로 여론형성과 선거 등 정치과정 차원에서 접근하였다. 특히 인터넷 상에서 참여・공유・개방의 웹 2.0을 기반으로 정보를 생산하는 소셜미디어의 등장은 쌍방향 소통 방식으로 이루어진다. 이는 정치적 여론과 이슈의 생성, 정치세력의 조직화까지 정치적 영향력에서 그 효과를 극대화, 일상화, 활성화시키는 잠재력을 보여주고 있다. 이러한 맥락에서 정치빅데이터의 개념을 정치적 목적, 혹은 정치 활동에 필요한 정보를 수집・저장하고 정치적으로 유의미한 ‘인사이트’를 찾아내어 새로운 형태의 정치적 가치를 추출해내는 일련의 과정으로 정의하였다. 정치빅데이터의 특징은 두 가지다. 사회현실을 파악하고 사회변화의 방향을 예측하여 그에 맞는 적절한 정책 혹은 정치적 방향을 세우는 것과 소셜미디어 등을 통한 개개인의 정치적 욕구를 표현하는 정치참여의 통로가 되고 있다는 점이다. 정치빅데이터의 활용 성공 사례로 평가를 받고 있는 2012년 미국 대통령선거 당시 오바마 캠프의 선거전략과 여론조사 활용을 통한 정치빅데이터의 정치적 유용성을 확인하였다. 분석구조는 유권자 데이터 집적 과정, 이를 기반으로 한 맞춤형 선거전략 사례 분석을 살펴보았다. 그 결과 정치빅데이터가 선거전략으로써 또한 여론분석으로써 유용하며, 유권자 데이터 집적 과정 자체가 또 다른 선거캠페인의 전 과정임을 확인하였다. 또한 집적과 분석을 통해 세대별, 연령별, 지역별 마이크로 타기팅 전략 수립의 가능성을 살펴보았다. 이는 정책공약을 확정짓는데도 유용하였지만 전략적 방향성을 바꾸는 데도 상당히 유용하게 활용되었다. 오프라인에서는 각 지역단위까지의 조직선거에 영향을 미쳤을 뿐 아니라 인터넷 상에서는 소셜미디어를 활용한 선거캠페인에 다양한 방식으로 유용하게 활용되었다. 향후 정치빅데이터의 적극 활용을 위해서는 유권자의 데이터 확보와 동시에 개인정보 침해를 방지하기 위한 대책 마련, 지속적인 경험의 축적과 이를 정확히 분석할 수 있는 전문가의 확보, 선거캠페인에서 소셜미디어 활용 여부를 놓고 정치빅데이터의 전부인양 생각하는 차원에서 넘어 정치빅데이터가 선거전략에서 패러다임의 전환을 일으키고 있다는 인식의 변화 등이 요구된다. This paper focuses on the usefulness of political big data in the political process of election strategy and opinion formation and analysis among the essence of political communication. This study analyzed the contents of Obama Camp's political big data at the time of US presidential election in 2012. Big Data, a key technology in the fourth industrial revolution, is the link between social change and technological innovation. It is a collection of all the information in the hyper-connectivity networks, created by combining technology with humans, society, nature and things. The vast volume of such big data must be based on insights into what to analyze and how to interpret, through collection, analysis and sharing before predicting the future. The same is true of big data in the political field. The development and spread of IT technologies is changing the paradigm of political processes by influencing the political perceptions and behaviors of political parties, politicians and voters alike. Access to big data in the political field is viewed as political communication in terms of ‘information about man’ and ‘interaction’. This study approached in the political process that is election and formation of public opinion as a political activity to acquire and sustain political power. In particular, the advent of social media, which produce information based on web 2.0 of participation, sharing, and openness over the Internet, consists of two-way communication. It demonstrates the potential to maximize, generalize, and activate the effects of political influence that can generalize political opinions and organize political power. In this context, this study defines the concept of political big data as a process that is gathering and storing information for political purposes or for political activities and extracting new forms of political value by finding politically meaningful “insights”. There are two features of this political big data. First, determine appropriate policies or political direction by understanding the reality of society and anticipating the direction of social change. Second, participate in politics by expressing individual political desires via social media. Obama Camp's election strategy at the time of the 2012 US presidential election, which has been evaluated as a successful example of political big data, and the political usefulness of political big data through the use of public opinion polls. Structural analysis is a customized campaign strategy based on the aggregation of voter's data and expert of big data. And it is an analysis by comparing polls and political big data by platform. It was confirmed that political big data was useful as electoral strategy and public opinion analysis, and that the process of gathering voter data was the predecessor of another election campaign. Also, it was looked at the possibility of creating micro-targeting strategies by age, generation, region through aggregation and analysis. In addition, this study found it possible to identify the public's opinion to develop an election strategy through analysis by comparing polls and political big data by platform. This was useful in confirming the policy promises but also used to change the strategic direction. Not only did offline influence organizational elections at each local level, but online they were also used in a variety of ways to be useful in election campaigns utilizing social media. In conclusion, we need to secure voter data and prepare to prevent personal information from being violated to make active use of political big data. Also, we need to have ongoing experience and gain expertise to analyze accurately. Finally, a shift in the perception that political big data is creating a paradigm shift in election strategies is needed.

빅테이터(Big Data) 융합예술의 세계적 양상과 전망분석

태혜신 한국무용과학회 2023 한국무용과학회지 Vol.40 No.1

Big Data is the first emerging core technology described in the World Economic Forum among the top 10 technologies. Internet of Things (loT), Robotics, 3D printing, artificial intelligence, new materials, 5G mobile communication, big data analysis, gene editing, virtual reality (VR), and augmented reality (AR) are the results of big data. These big data results are very useful in the field of society as a whole and art. However, there are not many cases of studying big data convergence art as creative art. Therefore, this study aims to provide basic data on big data convergence art and predict the future through research on the global development of big data convergence art. To this end, literature research was conducted using Internet data such as degree papers, academic journals and newspaper articles, websites, and blogs. The results of the study are as follows. The Internet of Things Art (IoT Art) area was hardly found in Korea as a starting stage. However, some Internet of Things artwork based on disruptive technology was being produced. On the other hand, AI creative art based on big data algorithms for each art area was developing innovatively and rapidly at home and abroad. Currently, AI works in the field of visual art and music are not distinguished from human works, and they surpass humans in that many works are created in an instant. In terms of big data, the visual field needs to build labeled image big data that can further develop the qualitative performance of AI creation, and the music field is very important to set optimal parameters. In the field of literature, AI is expanding its scope from phrase and sentence generation to scenarios, poems, and novels. They are creating their own new literary works by using existing literary works as big data. Of course, it is difficult to say that AI is engaged in independent creative activities rather than visual and music, but the era has already come when it takes on some of the roles of production and writer of completed works. In terms of big data, there is a high possibility that more interesting works will be created by expanding the size of the data. The dance field has developed from the dancing robot stage to the choreography AI stage. The robot's dance movements are more natural, delicate, and dynamically similar to humans than in the early stages. AI choreography is in its early stages and currently shows various motion samples, but AI auxiliary choreography activities are predicted through performance development in the future. In terms of big data, the most urgent thing at present is the work of big dataizing dancer movements. 빅데이터는 세계경제포럼에서 10대 기술 중 첫 번째로 서술한 떠오르는 핵심기술이다. 사물인터넷(loT), 로봇공학(Robotics), 3D 프린팅, 인공지능(AI), 신소재, 5세대 이동통신(5G), 빅데이터 분석, 유전자 편집, 가상현실(VR), 증강현실(AR) 등은 빅데이터의 결과물들이다. 이러한 빅데이터 결과물들은 사회 전반과 예술분야에서 매우 유용하게 활용되고 있다. 그러나 현재 창작예술로서 빅데이터 융합예술을 연구한 사례는 많지 않다. 이에 본 연구는 세계적인 빅데이터 융합예술 전개 양상 분석를 통해 빅데이터 융합예술의 기초자료 제공하고 미래를 전망해 보고자 한다. 이를 위해 2019년 12월부터 2022년 11월까지 3년간 저서, 학위논문, 학술지 및 신문기사, 홈페이지, 블로그 등의 인터넷 자료 등을 활용한 문헌 연구를 실시하였다. 연구결과는 다음과 같다. 사물인터넷 예술(IoT Art)영역은 시작 단계로 국내에서는 거의 찾아볼 수 없었다. 다만, 와해성 기술기반의 IoT Art작품은 일부 제작되고 있었다. 반면에 각 예술영역별 빅데이터 알고리즘 기반의 AI 창작예술은 국내외에서 혁신적, 급진적으로 발전하고 있었다. 현재 시각예술과 음악 분야의 AI 작품은 인간 작품과 구분되지 않으며, 일순간에 많은 작품들을 생성한다는 점에서는 인간을 능가한다. 빅데이터 측면에서 시각 분야는 AI 창작의 질적 성능을 더욱 발전시킬 수 있는 라벨링 된 이미지 빅데이터 구축 및 음악 분야는 최적의 매개변수 설정과 다양한 새로운 AI 알고리즘 개발이 필요하다. 문학 분야 AI는 문구, 문장 생성에서 나아가 시나리오, 시, 소설로 영역을 확장하며 기존 문학 작품들을 빅데이터로 활용해 새로운 문학 작품을 생성하고 있다. 시각예술과 음악 분야처럼 주체적 창작 활동을 한다고 보기 어렵지만, AI가 완성된 작품 생산 및 작가 역할을 일부 맡는 시대가 이미 도래했다. 빅데이터 측면에서는 자료 크기 확장과 AI 알고리즘을 세밀하게 다듬어야 한다. 무용 분야는 댄싱로봇 단계에서 안무 AI 단계로 발전했다. 로봇의 댄스움직임도 초기 단계보다 자연스럽고 섬세하며 역동적으로 인간과 비슷하다. AI 안무는 시작 단계로 현재는 다양한 움직임 샘플링을 보여주는 수준이지만 앞으로 성능 발전을 통한 AI 보조안무가 활동이 예측된다. 빅데이터 측면에서 현재 가장 시급한 점은 바로 무용수 움직임 빅데이터화 작업이다.

Improving Crisis & Emergency Management Capability of Government by Using Big Data Technology - China’s Response to the COVID-19 -

Linpei Zhai,Jae Eun Lee 위기관리 이론과 실천 2021 Crisisonomy Vol.17 No.9

The purpose of this study is to review the way how to use big data to improve the government’s crisis & emergency management capability to respond to public health crises and to suggest the future directions for improving the scientific application of big data analysis. This study classifies the specific manifestations of big data during the COVID-19 epidemic, and analyzes the advantages of using big data. Using big data to improve the government’s crisis management capabilities is mainly reflected in the following aspects: advancement of precision in response to the epidemic; promotion of the government’s internal and external cooperation; enhancement of the ability to respond to internet public opinion; promotion of the transformation of public decision-making from traditional experience to intelligent and scientific. In order to better integrate big data with public crisis governance, this study is concluded with a discussion of suggestions: improvement of big data application capabilities; enhancement of big data governance; people-oriented and paying attention to internet public opinion; innovation of public decision-making methods for big data governance.