NPR기반 누락 교통자료 추정기법 개발 및 적용

장현호,이태경,이영인,원제무,한동희 대한교통학회 2010 대한교통학회지 Vol.28 No.3

ITS (Intelligent transportation systems) collects real-time traffic data, and accumulates vest historical data. But tremendous historical data has not been managed and employed efficiently. With the introduction of data management systems like ADMS (Archived Data Management System), the potentiality of huge historical data dramatically surfs up. However, traffic data in any data management system includes missing values in nature, and one of major obstacles in applying these data has been the missing data because it makes an entire dataset useless every so often. For these reasons, imputation techniques take a key role in data management systems. To address these limitations, this paper presents a promising imputation technique which could be mounted in data management systems and robustly generates the estimations for missing values included in historical data. The developed model, based on NPR (Non-Parametric Regression) approach, employs various traffic data patterns in historical data and is designated for practical requirements such as the minimization of parameters, computational speed, the imputation of various types of missing data, and multiple imputation. The model was tested under the conditions of various missing data types. The results showed that the model outperforms reported existing approaches in the side of prediction accuracy, and meets the computational speed required to be mounted in traffic data management systems. 지능형 교통체계는 실시간 교통자료를 수집하고 방대한 양의 이력자료를 축적한다. 그러나 방대한 이력자료는 효율적으로 관리/이용되지 않고 있는 실정이다. ADMS와 같은 자료관리시스템이 도입되면서, 이력자료의 잠재적 활용성은 급격히 증대되고 있다. 그러나 자료관리스템의 교통자료는 다량의 누락자료를 포함하고 있다. 누락자료는 장기간에 걸쳐 빈번하게 교통자료를 이용할 수 없게 하기 때문에, 이력자료를 활용하는데 있어 주된 장애요인 중 하나이다. 따라서 누락자료 추정기법은 자료관리시스템에서 주요한 역할을 수행하게 된다. 이러한 한계를 극복하기 위하여, 본 연구에서는 자료관리스템에 탑재가 용이하며 이력자료에 포함된 누락자료를 추정하기 위한 누락자료 추정모형을 개발하였다. 개발모형은 비모수회귀식(NPR)을 기반으로 개발되었으며, 이력자료의 다양한 교통자료 패턴을 이용하고 현실적인 요구사항(변수 최소화, 연산속도, 다양한 형태의 누락자료 보정, 다중대체)을 충족하도록 설계되었다. 모형의 평가는 다양한 누락자료 형태의 상태에서 수행되었으며, 자료관리시스템에 탑재되기 위해 요구되는 정확도, 연산 수행속도에서 기존에 보고된 모형보다 우수한 성능을 보였다.

상업용 데이터센터의 비수도권 분산을 위한 입지요인 탐색적 연구

최대섭,강명구 한국도시행정학회 2024 도시 행정 학보 Vol.37 No.2

With the Fourth Industrial Revolution, the number of data centers has recently been rapidly increasing, with a concentration phenomenon occurring in the Capital Region. Accordingly, efforts are being made to disperse data centers outside of the Capital Region, but the problem is that the concentration of data centers in the Capital Region is still deepening. Existing studies have mainly focused on facility-related physical factors as location requirements for data centers. However, it is difficult to explain the location of data centers in Korea with these factors, and furthermore, it is difficult to This shows that the current policy of distributing data centers outside of the Capital Region is not successful. In this study, we sought to comprehensively understand the location factors of data centers by considering not only the physical factors of existing studies, but also the factors of data center consumers and workers(skilled labor). A total of 27 factors were examined, including 13 factors from the data center and corporate customer side and 14 factors from the skilled labor side. There are 53 commercial data centers that are the subject of this study, and most of them are concentrated in the Capital Region, an exploratory study was conducted rather than applying quantitative analysis based on a large amount of evenly distributed data. As a result of the study, the Capital Region, where most data centers are located, has many shortcomings in the physical aspects mentioned as important in existing studies. Rather, despite the fact that Non-capital Region have physical advantages, data centers are not distributed. Instead, it can be seen that the Capital Region shows strengths in factors related to the possibility of securing high-level technical personnel and the standard of living of high-level technical personnel. Because the data service industry requires rapidly changing, high-level technology and expertise, it is important to secure high-tech manpower, and furthermore, it is important to have living conditions that meet their high standard of living expectations. Dispersing data centers to Non-capital Region means that, in addition to simply industrial and physical aspects, Non-capital Region must be able to provide a high level of quality of life to high-level technical personnel. Although data centers do not have a large local revenue or direct employment effect, they can play an important role in balanced development in that they serve as a foundation for the region to advance into a high-value knowledge industry center. In order to distribute data centers outside of the Capital Region, it is essential to have a high-quality living base required by high-level technical talent.

빅데이터 비주얼라이제이션 사례분석

김형년(Kim, Hyungnyun) 인제대학교 디자인연구소 2014 Journal of Integrated Design Research (JIDR) Vol.13 No.4

“Every day 2.5 quintillion bytes of data are accumulating. 90% of the data we have now has accumulated over the past 2 years.” This is the first passage explaining big data on the IBM website. All actions of searching information, online shopping and uploading words and images on SNS is becoming a part of big data. However, “raw” data does not provide any significance. Movement pursuing to search the “significance” by reinterpreting an enormous number of sequences, Excel data, and text data is becoming an issue. This is where “data visualization” is introduced as a solution. It has provided a relationship between an enormous amount of randomly released data fragments with myself and has led to the attempt of discovering the hidden pattern and significance within. However, this has generally been achieved in fields related to information technology, and the attempt in the design aspect is difficult due to the high barrier of entry and approach concerning the technical aspect. This study carries significance in examining the current situation of visualization technology by analyzing “works produced with existing visualization technologies from visualization perspectives of big data” concerning a design aspect. This study is anticipated to become a prior study for UI and UX design developed in the big data visualization field by the participation of designers in the professional field of big data analysis and visualization technology, which are expected to increase in the future.

정부의 데이터 중심(data-driven) 채용 거버넌스 구축에 대한 시론적 연구: 미국 연방정부 사례를 중심으로

김정인,정상준 한국공공관리학회 2024 한국공공관리학보 Vol.38 No.1

Due to changes in the administrative environment such as digital transformation, data-driven human resource management has been receiving global attention. Accordingly, our study examined the U.S. federal government's data-driven hiring governance with respect to data-driven hiring infrastructure(data-driven hiring legal system and operational infrastructure), data-driven hiring propulsion system(data-driven hiring public-private partnerships, inter-ministerial collaboration, and operating system), and data-driven hiring follow-up management(data-driven hiringt performance management). As a result of the case analysis, the U.S. federal government enacted Federal Data Strategy, which is a top-level plan, to establish effective data-driven hiring governance, and was preparing a mid- to long-term action plan for federal government data management accordingly. It has been operating an integrated hiring digital platform(USAJOBS) since 1996, and has also been establishing a hiring partnership between OPM and the non-profit Partnership for Public Service since 2002. In addition, the U.S. federal government has established a collaboration system between the CDO Council, OPM, and each federal government agency; established and operated a data-driven hiring organization(Chief Data Officer); expanded the number of data experts(e.g., data scientists, hiring managers); and updated and disclosed regularly data-driven hiring status on the performance management website. The data-driven hiring governance of the U.S. federal government can contribute to establishing a collaborative system in the hiring processes around Korea's central personnel agency, systematically managing the status of data-driven hiring through transparent disclosure of data-driven hiring status, and constructing integrated public sector hiring governance by integrating government sectors and public institutions.

분산 데이터 상호운용을 위한 SQL/XMDR 메시지 기반의 Wrapper를 이용한 데이터 허브 시스템

문석재,정계동,최영근,Moon, Seok-Jae,Jung, Gye-Dong,Choi, Young-Keun 한국정보통신학회 2007 한국정보통신학회논문지 Vol.11 No.11

기업의 업무 환경이 지리적, 공간적으로 분산된 환경에서는 데이터 통합 시 발생되는 데이터 소스들을 표준 규칙과 메타데이터에 여과시켜서 중복성을 제거하고 데이터의 통합과 단일 뷰어를 제공하기에는 어려움이 따른다. 특히 이질적인 시스템이나 다양한 어플리케이션에서 나오는 대량의 데이터를 종류와 형식에 관계없이 호환이 가능하고, 지속적으로 정확한 통합 정보를 실시간으로 동기화할 수 있는 것이 관건이다. 따라서, 본 논문에서는 레거시 시스템간의 데이터 공유 및 교환에서 발생하는 의미적 상호 운용성의 문제점을 극복하는 SQL/XMDR 메시지 기반의 데이터 허브 시스템을 제안한다. 이 시스템은 데이터 협업 시 실시간으로 변화는 데이터를 일관성 있게 유지하기 위해서 질의 변환 방법인 메시지 사상 기법을 제시하여 이용한다. 이는 레거시 시스템들 간의 협업에 필요한 데이터를 공유 및 교환 하는데 실시간으로 변화하는 데이터를 일관성 있게 유지 할 수 있으며, 통합 검색 시 단일 인터페이스를 제공하여 각 시스템의 독립성을 유지하면서 데이터의 투명성과 가용성을 향상 시킬 수 있다. The business environment of enterprises could be difficult to obviate redundancy to filtrate data source occurred on data integrated to standard rules and meta-data and to produce integration of data and single viewer in geographical and spatial distributed environment. Specially, To can interchange various data from a heterogeneous system or various applications without types and forms and synchronize continually exactly integrated information#s is of paramount concern. Therefore data hub system based on SQL/XMDR message to overcome a problem of meaning interoperability occurred on exchanging or jointing between each legacy systems are proposed in this paper. This system use message mapping technique of query transform system to maintain data modified in real-time on cooperating data. It can consistently maintain data modified in realtime on exchanging or jointing data for cooperating legacy systems, it improve clarity and availability of data by providing a single interface on data retrieval.

Data-informed 디자인을 위한 데이터 수집 설계 도구 제안: 린 스타트업 환경을 중심으로

김유진,정영욱 인제대학교 디자인연구소 2023 Journal of Integrated Design Research (JIDR) Vol.22 No.4

Background : In the Fourth Industrial Revolution era, the rising importance of big data highlights the need for user data utilization in design. Despite this, UX designers in lean startups are encountering challenges in the initial stages of data collection. This gap exists despite the active theoretical research in data-driven design, signaling a lack of practical application methods. The study aims to explore major obstacles in the data collection phase of the lean UX process and to propose applicable solutions. Methods : For this study, a literature review was conducted to explore data-based design. It concentrated on examining various data types, how they are collected, and the real-world applications of these methods in design. It was identified that in early-stage startups, typically lacking data experts, UX designers have been undertaking significant roles in data collection design. To pinpoint the primary challenges in such environments, in-depth interviews with 12 designers were conducted. Using thematic analysis, 17 main themes and 6 key findings emerged. Subsequently, a design workshop with 4 UX designers from lean startups was organized to find effective solutions for these identified challenges. Results : The study concluded that a 'productivity tool', enabling indicator filtering and emphasizing real-time communication, is the most suitable solution. This tool includes features such as arranging elements based on time progression, aligning goals across the company and within teams, a design centered on both internal and external communication, and the ability to interact with external stakeholders. In line with this direction, a core scenario composed of 'goal setting', 'funnel definition', and 'event and property setting' was developed, and a prototype was designed for effective demonstration. Conclusion : The significance of this study lies in its exploration and proposition of solutions to challenges faced by UX designers in lean startup environments without data experts, particularly in the context of the burgeoning importance of data-driven design. The application of the proposed solution in practice is anticipated to enhance UX in the initial phases of data-driven design and to provide guidance for organizations in tailoring their environments based on the identified pain points.

경찰공무원의 데이터 리터러시와 직무역량간 관계 연구

윤현석(Yoon Hyun-seok) 한국보안관리학회(구:한국경호경비학회) 2024 시큐리티연구 Vol.- No.79

본 연구는 경찰공무원의 데이터 리터러시가 직무역량에 미치는 영향력을 분석하고 경찰 공무원의 데이터 리터러시 수준을 높이고 조직성과를 제고하기 위한 정책적 제언을 제시하는데 목적이 있다. 이를 위해 K광역시 및 J도 소속 경찰공무원 102명을 대상으로 조사연구를 실시하였다. 연구의 결과 첫째, 경찰공무원의 데이터 리터러시 수준은 3.58점, 직무역량 수준은 3.62점으로 높게 나타났으며, 일반적 특성에 따른 직무역량은 계급과 소속에서 차이가 있는 것으로 나타났다. 둘째, 데이터 의사결정과 직무역량 간의 상관관계가 가장 높게 나타났다. 셋째, 데이터 리터러시와 소속(시・도경찰청)이 직무역량에 영향을 미치는 변인으로 나타났다. 이에 경찰공무원의 데이터 리터러시 수준을 높이고 직무역량을 제고하기 위해서, 첫째, 데이터 기반 의사결정 조직문화를 구축하기 위해 데이터 검증체계를 강화하고 데이터를 업무에 적용할 수 있는 플랫폼 운영, 둘째, 데이터 활용을 지원하기 위한 제도 마련과 데이터 격차를 줄이기 위한 구성원 수준별 맞춤형 프로그램 마련, 셋째, 공공・민간부문의 데이터를 분석하고 부서나 관계기관 간 협력을 위한 클라우드 구축・운영 등을 제시하였다. 본 연구는 조사 대상을 특정지역의 일부 경찰공무원만 선정하여 조사했기 때문에 본 연구결과를 일반화시키기에는 한계가 있으며, 향후 보다 많은 지역의 경찰공무원을 대상으로 디지털 리터러시 수준을 향상시키기 위한 체계적인 프로그램 개발 연구와 직무역량에 영향을 미칠 수 있는 디지털 리터러시 변인들 간의 관계에 대해 연구가 이루어져야할 것이다. The purpose of this study is to analyze the influence of police officials' data literacy on their job capabilities and to present policy recommendations to increase the level of data literacy of police officials and improve organizational performance. For this purpose, a survey study was conducted targeting 102 police officers from K Metropolitan City and J Province. As a result of the study, first, the data literacy level of police officials was high at 3.58 points and the job competency level was high at 3.62 points, and job competency according to general characteristics was found to differ depending on rank and affiliation. Second, the correlation between data decision-making and job competency was the highest. Third, data literacy and affiliation (city/provincial police agency) were found to be variables affecting job competency. Accordingly, in order to increase the level of data literacy and enhance job capabilities of police officials, first, strengthen the data verification system to establish a data-based decision-making organizational culture and operate a platform that can apply data to work, second, utilize data. Third, it proposed the establishment of a system to support and a customized program for each member level to reduce the data gap, and third, analysis of data in the public and private sectors and construction and operation of a cloud for cooperation between departments and related organizations. Because this study only selected some police officials in a specific region as its research subjects, there are limitations in generalizing the results of this study. In the future, research is needed to develop a systematic program to improve the level of digital literacy for police officials in more regions. Research should be conducted on the relationship between digital literacy variables that can affect job competency.

데이터 기반 사용자 여정 분석 도구 UX 디자인 개선 방안 제안 ­뷰저블 애널리틱스(Beusable Analytics)를 중심으로­

정지현,김서연,박민희,이지현 인제대학교 디자인연구소 2022 Journal of Integrated Design Research (JIDR) Vol.21 No.4

Background : With the recent growth of big data and the advancement of data analytics, the importance of data-informed UX design is being highlighted. As the need for more sophisticated analyses on user needs and behavior patterns, a great variety of analysis methods were developed. But, there is a lack of study that focuses on detailed data exploration and analysis based on interaction designs that implement such concepts for the moment. Methods : Beusable Analytics, data-informed user journey analysis tool in South Korea, as a research subject to improve user experience based on data analysis. First, this study conducted literature review to understand about the User Journey Map, Funnel Analysis, Data Visualization types and Flow factors for Data Analytics. data visualization types and interaction methods of data informed user journey analysis tools were analyzed. Afterwards, expert evaluation was conducted, and major problems and design improvements were proposed by analyzing the evaluation contents and measuring priorities. Results : Finally, four improvements were proposed as wireframe and key path scenario to improve the ‘limitation of the overall view of the entire journey', ‘lack of storytelling of the journey’, ‘Difficulty in recording and interpreting data‘ and ‘difficulty in identifying variability'. Conclusion : This study proposes ways to improve user experience by considering User Experience such as UI (User Interface) and Interaction for UX designers who want to derive insights by analyzing user journey data. Analysis results of user journey analysis tools and expert evaluations are meaningful in that they confirmed the behavioral patterns and functional requirements of practical UX designers during data analysis. It is expected to be used as a useful resource for the usefulness of the existing user journey analysis tool has been improved through the design improvement plan, and it is expected to be applied and used as an additional function of the user journey analysis tool that provides not only viewable analytics but also funnel analysis. 연구배경 : 최근 빅데이터 관련 기술의 성장과 데이터 분석 솔루션의 고도화로 인해 데이터 기반 UX 디자인의 중요성이 더욱 크게 부각되고 있다. 고객의 니즈와 행동 패턴의 정교한 분석이 점점 더 중요해지며, 다양한 분석 방식이 개발되었지만 국내에서는 아직까지 이를 구체화한 분석 도구의 개발과 인터랙션 디자인 기반 데이터 탐색 및 분석에 초점을 맞춘 연구는 미비한 실정이다. 연구방법 : 본 연구는 데이터 기반 사용자 여정 분석 도구의 사용자 경험 향상을 위한 디자인 개선 방안을 제안하고자 상용화되어 있는 사용자 여정 분석 도구 중 국내 서비스인 뷰저블 애널리틱스(Beusable Analytics)를 연구 대상으로 선정하였다. 우선 문헌 연구를 통해 사용자 여정 지도와 퍼널 분석에 대해 파악하고, 국내외 사용자 여정 분석 도구의 데이터 시각화 유형 및 데이터 분석을 위한 인터랙션 방식에 대해 분석하였다. 전문가 평가를 진행하여 뷰저블 애널리틱스의 사용성을 진단하고, 평가 내용 분석과 우선순위를 측정하여 주요 문제점과 디자인 개선 사항을 제안하였다. 연구결과 : 결과적으로 ‘여정 전체 조망의 한계’, ‘여정의 스토리텔링 전달 부족’, ‘데이터 기록 및 해석의 어려움’, ‘변동성 파악에 대한 어려움’ 총 4가지 주요 문제점과 디자인 개선 사항의 와이어프레임(Wireframe)과 핵심 경로 시나리오(Key path scenario)를 제안하였다. 결론 : 본 연구는 웹 페이지 내 사용자 여정 데이터를 분석하여 인사이트를 도출하고자 하는 IT 실무자가 효율적으로 데이터를 탐색하기 위한 UI(User Interface) 및 인터랙션(Interaction) 등의 사용자 경험적 측면을 고려하여 경험 향상 방안 제안을 목적으로 진행되었다. 전문가 평가 분석 자료와 상용화 되어 있는 사용자 여정 분석 도구의 시각화 방식 및 인터랙션 측면의 분석 결과는 데이터 분석 시의 실무 UX 디자이너와 기획자의 행동 패턴과 기능 요구사항을 확인하였다는 것에 의의가 있으며, 동료 연구자들에게 유용한 자료로 활용될 것으로 기대된다. 또한, 디자인 개선안을 통해 기존 사용자 여정 분석 도구의 유용성을 높였으며, 이는 뷰저블 애널리틱스뿐만 아니라 퍼널 분석 등을 제공하는 사용자 여정 분석 도구의 발전방향 수립 시 참고할 수 있을 것으로 기대한다.

2022개정 과학과 교육과정에 나타난 데이터 기반 탐구활동 분석

윤진아,남윤경 이화여자대학교 교과교육연구소 2024 교과교육학연구 Vol.28 No.4

This study explores the purpose and scope of data use in inquiry activities by analyzing the data-based inquiry activities in the essential inquiry activities presented in the 2022 revised national science standard. To achieve this goal, the researchers first defined scientific inquiry elements based on a literature review and established analysis standards for data-based scientific inquiry activities. Then, a list of essential research activities was selected. Lastly, using the analysis criteria, the researchers examined the inquiry process skills and data utilization possibilities and sources for the required inquiry activities secondary science secondary subjects in the 2022 national science standard. The analysis revealed that the most common basic process skills in data-based activities were prediction, reasoning, and measurement. The most frequently integrated process skills involved data conversion, data analysis, and interpretation. In addition, data sources used in research activities were classified into those that utilize public institution data APIs, big data, etc., and those that collect data directly, and the use of existing data mainly focuses on big data. The results indicated that the inquiry activities in the 2022 revised national science standard primarily involve the analysis and interpretation of provided data, rather than student-initiated data collection and investigation design. To ensure that these essential inquiry activities enhance students' knowledge information processing competency, the study suggested the need for multifaceted efforts, including textbook writing and professional development for in-service science teachers, to implement data-based inquiry effectively.

데이터 안보 시대의 사이버 안보 쟁점과 전환적 특징

윤정현 한국정치정보학회 2024 정치정보연구 Vol.27 No.3

Today, data has become an indispensable resource for a digitally transformed society. As data has been recognised as a resource with inherent economic and security value, it has also been argued that the control and utilization of data should be approached from a security perspective. Data has emerged as a key determinant of order, competition, and security interests in cyberspace. As digital transformation becomes more advanced, cyberspace is expanding. This trend is accelerated by technological innovation and the expanding transformation of key actors in cyberspace. Cyber attack behaviour is also evolving in response to these changes. While "information and data uselessness" attacks, such as simultaneous hacking targeting technical and military specialist groups and leaking, stealing, or deleting military secrets, have been the main challenge, we are now seeing more frequent attack types that threaten civilians and unspecified multi-stakeholders, such as manipulation, contamination, and influence operations of civilian and personal information and data, combined with social engineering. In light of this changing landscape, we need to shift our approach in the following ways. First, the evolution of cyber attacks shows a shift in targets. We need to strengthen the protection of not only infrastructure & network &software, but also unstructured & multiple personal data. Second, a shift to multi-layered governance, including private and multi-stakeholder actors as responders. Third, we need to prepare for a complex competitive landscape that takes into account future data security mechanisms.