스마트폰 CMF 디자인 개발에서 빅데이터(big data) 분석기술 활용방안 연구

오인균(Oh, In Kyun),김영미(Kim, Young Mi),차성욱(Cha, Sung Wook) 한국디지털디자인협의회 2014 디지털디자인학연구 Vol.14 No.4

빅데이터는 방대한 데이터 속에 숨겨진 정보를 찾아내는 것을 말하며, 현재 경제 트렌드에서 가장 많이 등장하는 키워드 중 하나이다. 경제 트렌드에서 빅데이터가 주요 키워드라면 디자인분야에서는 소비자 감성과 경험이 주요 키워드이며, 스마트폰 디자인에서는 이러한 소비자 감성과 경험을 CMF 디자인을 통해서 표현하고 있다. 따라서 본 연구는 CMF 디자인 개발에 이러한 빅데이터 활용방안을 제안하는 것을 목적으로 총 3단계의 과정을 거쳤다. 1단계에서는 문헌연구 중심으로 빅데이터에 대한 이론적 정의를 바탕으로 빅데이터를 적용한 디자인분야의 선행연구를 조사, 분석을 하였다. 또한 관련연구를 통하여 스마트폰 CMF 디자인개발 프로세스와 선행연구를 정리하였다. 2단계에서는 객관적인 연구결과 도출을 위하여 설문조사와 그룹인터뷰(FGI)를 실시하였다. 설문조사결과 CMF 디자이너들의 빅데이터에 대한 이해도는 중간정도였으며, 업무 활용가능성은 높게 생각하는 것으로 조사되었다. 또한 CMF 디자이너들은 프로세스에서 빅데이터 활용가능성이 제일 높은 단계로 Design Research단계를 뽑았다. 3단계에서는 이러한 조사결과와 그룹인터뷰(FGI)를 바탕으로 CMF 디자인개발에서의 빅데이터 활용방안을 작성하였다. 활용방안은 CMF 디자인개발 프로세스에서 각 단계별로 활용할 수 있는 빅데이터 분석기술을 접목하였다. 이러한 빅데이터 활용방안은 프로세스를 중심으로 구축되어 실무에서의 활용가능성을 높인 것이 장점이며, 이를 통해 업무 효율성을 높이고 좀 더 소비자들의 니즈를 담은 CMF 디자인 개발에 도움이 될 것으로 예상된다. Big data will find the information that was hidden in a large data. Big data is a keyword that appears the most in the current economic trends. If the big data is a major keyword in economic trends, experience and sensibility of the consumer is an important keyword in the design. The design of the smart phone, it have to express and experience sensibility through the CMF(Color, Material, Finishing). Therefore, we aim to develop CMF design, we propose a big data utilization of these methods, and through a process of three stages in this study. In first step, as a method of literature research, investigate the previous studies of big data applications and theoretical definition of big data and were analyzed. In addition, researchers was to organize the process of developing smart phone CMF design. In second step, researchers performed focus group interviews and questionnaire survey for the research results derived objective. It was found that the degree of understanding for the big data of CMF designer is moderate results of the survey, it is thought very likely take advantage of the business. In addition, CMF designer chose the Design Research step at the stage most likely of the big data utilized in the design process. In final step, based on the focus group interviews and survey results, we created a big data utilization plan of the development of CMF design. In the development process of CMF design, leverage proposal, a fusion of big data analysis technique which can be used at each step. We combine the ability to take advantage of each step in the design development process, CMF Utilization of Big Data analysis techniques. The advantage to this process is built around the Big Data Application of the enhanced availability of in practice. And we expected by this, increase the efficiency of business, and help in the development of CMF design that incorporates the needs of more consumers.

데이터 의미 변화에 따른 디자인 프로세스에서 데이터 역할 및 활용 방향 제안

이주연,정의철 한국디자인트렌드학회 2020 한국디자인포럼 Vol.25 No.2

Background The design process is the process of understanding the user and suggesting a concept. In this process, various data are collected, analyzed, interpreted, and the design inspiration is obtained. In the traditional design process, data was regarded as a reference material, but as the design process gradually formed a view of viewing as a knowledge creation activity using data, attempts to utilize data as a material for design concept creation by utilizing various data collection technologies. This study aims to consider the role of data in the design process and to suggest directions for its use. Methods Theoretical considerations such as the meaning of data in design and the concept of big data that played a big role in these semantic changes will be conducted as a literature study. Through a case study in data-driven design, we consider the process of using data as a creative material, and present a model that can conceptually explain the role of data in the design process according to the change in the meaning of data. Result The change in the direction in which data can be used in the design process due to changes in data roles and usage methods was proposed as the following two points. The process of data semantic evolution is reflected in the design process as it is, leading to a change in the design process, and this change in data utilization is leading to the evolution of user participation. Conclusion In this study, we looked at the changes in data utilization and its cases brought about by the evolution of the meaning of data in the design process, and redefined the changes in the design process from the perspective of data. It is expected that this study will be a basic study that can present a data utilization frame in future product and service projects. 연구배경 디자인 프로세스는 사용자를 이해하여 컨셉을 제안하는 과정이다. 이 과정에서 다양한 데이터를 수집, 분석, 해석하고 이를 통해 디자인 영감을 얻게 된다. 전통적 디자인 프로세스에서 데이터는 참고자료로 간주가 되었으나, 점차 디자인 프로세스가 데이터를 활용한 지식 창조 활동으로 보는 관점이 형성되면서, 다양한 데이터 수집 기술을 활용하여, 데이터를 디자인 컨셉 창작의 재료로 활용하려는 시도가 많아지고 있다. 본 연구는 디자인 프로세스에서 데이터의 역할을 고찰하고 활용 방향을 제안하는 것을 목표로 한다. 연구방법 디자인에서 데이터의 의미와 이러한 의미 변화에 큰 역할을 한 빅데이터의 개념 등의 이론적 고찰은 문헌 연구로 진행되며, 데이터 의미 변화에 따른 디자인 프로세스에서의 데이터의 역할에 대한 연구를  4단계로 정리하여  제시한다. 데이터 기반 디자인에서의 사례 연구를 통해  데이터를 창작의 재료로 활용하는 프로세스를 고찰하며 데이터 의미 변화에 따른 디자인 프로세스에서 데이터의 역할 변화를 개념적으로 설명할 수 있는 모형을 제시한다. 연구결과 데이터 역할 및 활용 방법의 변화로 디자인 프로세스에서 데이터를 활용할 수 있는 방향의 변화를 다음의 두 가지의 논점으로 제시하였다. 데이터 의미 진화 과정이 디자인 프로세스에 그대로 반영되어 디자인 프로세스의 변화를 이끌고 있으며, 이러한 데이터 활용의 변화가 사용자 참여 형태의 진화를 가져오고 있는 것이다. 결론 본 연구에서는 디자인 프로세스에 있어서 데이터 의미의 진화가 가져온 데이터 활용의 변화와 그 사례를 살펴보고 디자인 프로세스의 변화를 데이터의 관점에서 재정의 하였다. 본 연구는 추후 제품, 서비스 프로젝트에서의 데이터 활용 프레임웤을 제시할 수 있는 기반연구가 될 것으로 기대한다.

데이터 기반 UX 디자인 교육을 위한 사례기반학습(CBL) 프로그램 개발 및 적용

김서연(Seo Yeon Kim),이지현(Ji Hyun Lee) 한국디자인리서치학회 2023 한국디자인리서치 Vol.8 No.1

다양한 종류의 데이터를 활용하는 것에 익숙해짐에 따라 디자인 산업 분야에서도 디자인 과정에서 데이터를 디자인 컨셉 창작의 재료로 활용하려는 시도가 많아지고 있다. 데이터는 보다 객관적인 인사이트를 제공할 수 있으므로 디자이너는 데이터를 통해 올바른 방식으로 제품을 디자인할 수 있다. 최근 데이터 기반 디자인에 관하여 다양한 연구가 진행되고 있다. 데이터 기반 디자인의 분류라고 할 수 있는 Data Driven, Informed, Aware 디자인의 개별적인 개념을 중심으로 진행된 연구들이 있으나 데이터 기반 디자인을 실무에서 활용하는 방식으로 분류하여 진행한 국내 연구는 미비하다. 따라서 데이터 기반 디자인 경험이 부족한 초심자의 경우 데이터 기반 디자인 방법을 구분하여 활용하는 것이 쉽지 않다. 본 연구는 데이터를 활용한 디자인이 익숙하지 않은 사용자가 데이터를 활용하여 의사결정하는 방법에 대한 마인드셋을 갖추고 정량 데이터와 의사결정 간의 관계성을 학습하는 것을 목표로 하였다. 사례 기반 학습을 활용하여 초심자의 이해를 돕는 교육 프로그램을 설계하고 초심자도 쉽게 참여할 수 있는 사례지와 기준을 활용하여 데이터 기반 디자인의 프로세스와 유형을 학습하는 데 도움이 되도록 하였다. 교육 프로그램은 데이터 기반 디자인 초심자를 대상으로 교육을 진행하고, 전문가 평가를 거쳐 유용성을 검증하였다. 본 연구에서 개발한 교육 프로그램은 초심자가 데이터 기반 디자인이 어떤 방식으로 시행되는지 이해하고 알아보는 방안으로 활용될 수 있을 것으로 기대된다. As people get used to using various types of data, more and more attempts are being made to use data as a material for creating design concepts in the design process. Because data can provide more objective insights, designers can design products in the right way through data. Recently, various studies have been conducted on data-based design. There are studies focused on the individual concepts of Data Driven, Informed, and Aware design, which can be said to be a classification of data-based design, but domestic studies conducted by classifying data-based design in practice are insufficient. Therefore, it is not easy for beginners who lack data-based design experience to use data-based design methods separately. This study aimed to learn the relationship between quantitative data and decision-making by having a mind set on how users who are not familiar with the design using data make decisions using data. Case-based learning was used to design educational programs that help beginners understand, and case papers and criteria that beginners can easily participate in to help them learn the processes and types of data-based design. The educational program conducted education for beginners in data-based design, and verified its usefulness through expert evaluation. The educational program developed in this study is expected to be used as a way for beginners to understand and find out how data-based design is implemented.

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.

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.

디자인 교과과정에서의 데이터 문해력 교육에 관한 연구 –디자인-데이터 융합 교과 개발 사례를 중심으로

이현진 한국콘텐츠학회 2022 한국콘텐츠학회논문지 Vol.22 No.5

This study explores convergence curriculum for design and data science, and applies data science knowledge on undergraduate design classes for designer's data literacy. First, related studies about data literacy education for non-data science major’s, and data driven design project cases are explored, then design competency and data competency based on NCS are studied. Then this study developed 3 step design-data convergence curriculum model for designers’ data literacy. The curriculum model is applied on case study classes, which are Big data and UX design(2) classes. The learning results and student's feedback of the case study classes are collected and analyzed to prove the design-data convergence curriculum, and the results provide findings and implications of the design-data convergence class case study. 본 연구는 향후 디자이너의 업무 역량에 매우 중대한 역할을 하게 될 데이터 문해력 확보를 위하여 디자인 대학 교과과정에서의 데이터 문해력 관련 교육목표와 교과 구성, 교육 내용을 연구하였다. 연구의 방법은 먼저 비전공자를 위한 데이터 문해력 교육의 사례들과 디자인 실무 현장의 데이터 기술 활용 현황을 살펴보았고, 현장 직무 중심 디자인 역량에 대한 선행 연구와 디자인 프로세스 모델을 바탕으로 디자인 분야에서 요구되는 데이터 관련 전공 능력을 도출하였다. 그리고 NCS에 기반한 빅데이터 기획과 분석 분야의 교육 내용을 조사하여, 디자인 전공 능력에 필요한 데이터 기술 관련 교과 내용을 연계하여 디자이너를 위한 데이터 문해력 교육 모듈을 3단계의 디자인-데이터 융합 교과 모델로 구성하였다. 개발된 융합 교과 모델을 바탕으로 필요한 단위 교과목과 강의 계획, 과목 간 연계 구조를 개발하였으며, 초, 중급 수준의 디자인-데이터 융합 교과목을 운영한 사례 연구를 통하여 교육모델의 교육 내용과 교육 성과를 검증하였다. 그리고 교과 운영 사례 연구의 발견 점들을 바탕으로 디자이너를 위한 데이터 문해력 교육의 구체적 실천 방안을 제시하고, 사례 연구의 한계를 명시하였다.

디자인 직군과 경영 직군의 데이터 활용 방식 분석 연구 : 문제의 발견과 해결 과정에서의 데이터 제공 디자인(Datainformed Design) 관점으로

이민화(Minhwa Lee),이연준(Younjoon Lee) 한국디자인학회 2024 디자인학연구 Vol.37 No.4

Background : This study aims to analyze how practitioners in the ‘Design’ and ‘Business’ fields utilize data from a ‘Data-informed Design’ perspective in order to propose a co-design direction for those practitioners to discover and solve problems centered on data. To achieve this, the data interpretation and ideation processes of design and business practitioners are observed, and the results are quantified. Methods : Through empirical research, we observed the process in which design practitioners and business practitioners analyze data and generate ideas. Subsequently, we separated the interpretation process from the ideation process for analysis. In the interpretation process, we conducted protocol analysis and classified the topics into ‘Business Management’, ‘Design Output’, ‘Customer Response’, and ‘Infra & Structure’. We compared the frequency and duration of speech between design and business practitioners for each topic. For the ideation process, we evaluated the ‘Novelty’, ‘Usefulness’, and ‘Commercial Appeal’ of ideas generated by design and business practitioners and we compared the results. Results : The following is an analysis of the data interpretation process. By topic, designer practitioners spoke more frequently and for longer durations than business practitioners about ‘Design Output’, while business practitioners spoke longer than designer practitioners about ‘Business Management’. Furthermore, while designer practitioners tended to swiftly approach problems across topics based on their knowledge, business practitioners relied on data and focused on ‘Business Management’. The data-informed ideation process was analyzed. Although there were differences in when and how the two groups utilized numerical and visual data, both groups scored higher on ideas based on numerical data. When analyzing data-informed ideation by topic, differences were observed in how the two groups utilized numerical and visual data, as well as in the evaluation of ideas by topic. Conclusions : This study analyzes the characteristics of design practitioners and business practitioners when interpreting and generating ideas based on the same data, and derives considerations for ‘Datainformed co-design’ for them.

Challenges of Designing with Open Data: The Case of Cultural Data

이문환 한국디자인학회 2019 디자인학연구 Vol.32 No.3

Background While the promise of a data-driven economy lies to a large extent in the development of new services and start-up companies, the results, in terms of products and services created, remain below open-data promoters’ expectations. Transforming the promise of a data-driven economy into a reality requires the exploration of difficulties in the field from a design-process perspective. Methods We conducted a design workshop and analyzed how general designers used open data in the design process. The study lasted four weeks in which participant groups worked on the four phases of the design process. Over the first two weeks, we asked participants to scan the open data sets. Then, considering usable open data, as well as possible target users and their problems, the groups of participants defined their design spaces. The participant groups were asked to concretize design concepts that utilized open data and deliver final outcomes after another two weeks. Results In our study, we found that participants used open data as a new material. However, their data use was limited to listing existing data or simply editing data without imposing deep and diverse modifications. Furthermore, they tended to consider the immediate availability of the most important factor and therefore preferred open data that they deemed easy to use on the basis of existing design cases. Conclusions Our findings yielded several practical design implications, such as the urgent need for improved data-searching interfaces, design methods with high data literacy, and enhanced data infrastructure at the governmental level. The study’s results and design implications will hopefully inspire other designers and researchers to develop open data ecosystems that are more designer-friendly. Background While the promise of a data-driven economy lies to a large extent in the development of new services and start-up companies, the results, in terms of products and services created, remain below open-data promoters’ expectations. Transforming the promise of a data-driven economy into a reality requires the exploration of difficulties in the field from a design-process perspective. Methods We conducted a design workshop and analyzed how general designers used open data in the design process. The study lasted four weeks in which participant groups worked on the four phases of the design process. Over the first two weeks, we asked participants to scan the open data sets. Then, considering usable open data, as well as possible target users and their problems, the groups of participants defined their design spaces. The participant groups were asked to concretize design concepts that utilized open data and deliver final outcomes after another two weeks. Results In our study, we found that participants used open data as a new material. However, their data use was limited to listing existing data or simply editing data without imposing deep and diverse modifications. Furthermore, they tended to consider the immediate availability of the most important factor and therefore preferred open data that they deemed easy to use on the basis of existing design cases. Conclusions Our findings yielded several practical design implications, such as the urgent need for improved data-searching interfaces, design methods with high data literacy, and enhanced data infrastructure at the governmental level. The study’s results and design implications will hopefully inspire other designers and researchers to develop open data ecosystems that are more designer-friendly.

공공디자인 진흥계획 내 공간정보 데이터의 활용에 관한 연구

김성훈,이현성,김주연 한국공간디자인학회 2023 한국공간디자인학회논문집 Vol.18 No.7

(Background and Purpose) Since the early to mid-2000s, the government has recognized the significance of design as a catalyst for economic growth, shifting its focus towards fostering creativity. In recent times, the proliferation of large-scale data and advanced spatial analysis tools, such as OPENAI, has led to a substantial increase in the demand for data across various sectors, with nearly 80% of this data comprising spatial information. South Korea is now launching the 'Digital New Deal' as a comprehensive 'National Innovation Project' to combat the economic challenges posed by COVID-19 and usher in a digital transformation across the economy and society. This study aims to examine the state of data utilization, analysis, outcomes, trends, and challenges, with a particular emphasis on spatial information, which forms the bulk of data in the crucial 'Public Design Promotion Plan.' The goal is to propose the necessary infrastructure and prerequisites for the success of this promotion plan. (Method)While numerous regions have initiated public design initiatives, this study focuses on the districts of Seoul, which have been at the forefront of public design policies. Seoul established the Design Headquarters, an organization spearheading urban and public design-related policies. The research methodology involves organizing and analyzing data used in the promotion plan, formulating strategies and projects, and establishing a logical framework through a preliminary survey. Non-spatial data, such as photographs, is excluded, while GIS data and mapping data are collected and analyzed. The collected data types are categorized based on five environmental criteria used in the preliminary survey. After gaining insights into the characteristics of the departments responsible for public design promotion plans in Seoul districts, the study examines data-driven clusters, trends in data utilization, and usage patterns. (Results)Despite similarities in spatial information, such as GIS and mapping data used in public design promotion plans across Seoul districts, the extent of utilization varies significantly among the three groups clustered by GIS data. Most data analyses are presented in a narrative format, often lacking clarity in the analysis process and standards, highlighting the need for objectivity and precise data construction. (Conclusions)This study confirms that the utilization of GIS data is contingent on the capabilities of service providers and the requirements of ordering departments, with many districts relying on public data platforms. This reliance implies that entities promoting public design plans struggled to directly construct and employ public design data due to various limitations, potentially leading to uniform public design promotion plans. Consequently, the creation of unique public design data serves as a cornerstone for the identity and potential of the public design promotion plan, a responsibility that the government should champion.

Advanced Information Data-interactive Learning System Effect for Creative Design Project

Sang Woo Park,Inseop Lee,Junseok Lee,설상훈 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.8

Compared to the significant approach of project-based learning research, a data-driven design project-based learning has not reached a meaningful consensus regarding the most valid and reliable method for assessing design creativity. This article proposes an advanced information data-interactive learning system for creative design using a service design process that combines a design thinking. We propose a service framework to improve the convergence design process between students and advanced information data analysis, allowing students to participate actively in the data visualization and research using patent data. Solving a design problem by discovery and interpretation process, the Advanced information-interactive learning framework allows the students to verify the creative idea values or to ideate new factors and the associated various feasible solutions. The student can perform the patent data according to a business intelligence platform. Most of the new ideas for solving design projects are evaluated through complete patent data analysis and visualization in the beginning of the service design process. In this article, we propose to adapt advanced information data to educate the service design process, allowing the students to evaluate their own idea and define the problems iteratively until satisfaction. Quantitative evaluation results have shown that the advanced information data-driven learning system approach can improve the design project -based learning results in terms of design creativity. Our findings can contribute to data-driven project-based learning for advanced information data that play a crucial role in convergence design in related standards and other smart educational fields that are linked.