All Issue

2019 Vol.7, Issue 3 Preview Page

Research Article

September 2019. pp. 107-115
4차 산업혁명을 이끌어가고 있는 주요 기술 중 하나인 데이터 가시화 기술은 빅데이터(Big Data)와 함께 많은 발전을 이루었다. 최근 데이터의 성격이 인터랙티브 미디어(Interactive Media)로 발전함에 따라 데이터 가시화 또한 사용자 경험의 질을 높이는 것을 고려하게 되었고, 사용자와 데이터간의 상호작용이 가능한 인터렉티브한 가시화가 주목을 받고 있다. 인터랙티브 그래프는 사용자가 그래프를 자유롭게 조작하거나 원하는 시점에서 그래프를 살펴 볼 수 있는 등 직관적이고 효율적인 정보 지각과 인지가 가능하다는 장점이 있다. 본 논문에서는 Plotly 패키지와 R-Studio와 산포(Scatter) 가시화 기법을 이용하여 1952년부터 2007년까지의 기대수명과 1인당 GDP의 통계 데이터를 3D 애니메이션 형태의 인터랙티브 가시화 콘텐츠를 구현하였다. 가시화된 인터랙티브 그래프는 선택과 재정렬, 회전과 확대, 필터링 기법을 사용하였다.
Data visualization technology, one of the key technologies leading the fourth industrial revolution, has made great progress with Big data. Recently, as the nature of data has developed into interactive media, data visualization has been considered to improve the quality of the user experience, and interactive visualization capable of interacting with users and data has been attracting attention. Interactive graphs have the advantage of intuitive and efficient information perception and recognition, allowing the user to manipulate the graph freely or to look at the graph at any point in time. In this paper, we implemented 3D visualization of interactive visualization contents of statistical data of life expectancy and per capita GDP from 1952 to 2007 using Plotly package, R-Studio, and scatter visualization technique. The visualized interactive graph uses selecting and reordering, rotation and expansion, and filtering techniques.
  1. Mayer-Schonberger and Viktor, “Big data : a revolution that will transform how we live work and think.”, JOHN MURRAY PUBLISHERS , 2013.
  2. Lee Seong Chun, Lim Yang-su, and An Minji, "Big data, secret key to opening the future", KT Economic Research Institute, 2011.
  3. Wikipedia. data visualization. available:
  4. Park Sun Hee, “Implementation of public data contents using big data visualization technology – map visualization technique”, Journal of the Digital Contents Society of Korea, Vol.18, No.7, pp. 1427-1434, 2017.
  5. Kim Young-woo, “Do it! easily learn R data analysis”, EasysPublishing, pp. 289-290, 2017.
  6. Shin Hee-sook, “Information visualization technology and information expression technology for the visually impaired”, Electronic Telecommunications Trend Analysis, Vol. 28, No. 1 pp. 81-91, Feb. 2013.
  7. M K Beyer and D Laney, “The Importance of big data: a definition”, Gartner, June 2012.
  8. J Manyika, “ Big data: The next frontier for innovation, competition, and productivity”, Mckinsey Global Institute, Insight s& Publications, May 2011.
  9. J Gantz and D Reinsel, “Extracting value from chaos”, I DC, June 2011.
  10. Son Jin Suk, “Media art using data visualization: focused on big data visualization art,”,, Soongsil University, pp.9-13, June 2015.
  11. Shin Shin Ae, "2013 Big data institutional commodations for Creative Economy", Korea Information Society Agency Big Data Research Center, 2014.
  12. Shin Shin Ae, "The guideline for big data analysis and usage version 1.2", Korea Information Society Agency Big Data Research Center, 2012.
  13. Jeong Ji Seon, "A new cost generation engine, big data : new possibilities and strategies", National Information Society Agency, NIA, 2011.
  14. Naver knowledge encyclopedia. interactive. available:
  15. Park O Reum, “A study on the expression form of interactive diagram”,, Kyung Hee University, 2012.
  16. Kwak Min Koo, “(A) case study on interactive data visualization : focused on digital news media, Bloomberg and The New York Times”,, Sungkyunkwan University, 2018.
  17. Kang Sang Koo and Nam Doo Hee, “Multiple interactive visualization techniques for information”, Korea ITS Association Journal, Vol. 11, No. 5, 2012.10.12815/kits.2012.11.5.056
  • Publisher :The Society of Convergence Knowledge
  • Publisher(Ko) :융복합지식학회
  • Journal Title :The Society of Convergence Knowledge Transactions
  • Journal Title(Ko) :융복합지식학회논문지
  • Volume : 7
  • No :3
  • Pages :107-115