A Data Visualization System for Considering Relationships Among Scientific Data

  • Jangwon Gim
  • Yunji Jang
  • Yeonghun Chae
  • Hanmin Jung
  • Do-Heon Jeong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9191)


With the recent explosive increase in the amount of web-based scientific data in big data environments, various researcher support systems have been developed to help discover desired scientific data and search insights. Scientific and researcher-related data are also applied to social networking services, thus promoting inter-researcher networking. However, much time and effort is put into big data mining to extract information customized to researchers’ specific needs. Moreover, systems that facilitate information extraction by schematizing various inter-data relationships are absent. In this paper, we propose a system that facilitates relevant information extraction from scientific data and provides intuitive data visualization. Such data visualization allows efficient relationship expression between scientific data (relationships between researchers, acronyms and technical terms, and synonyms of a technology name), and provides an author disambiguation interface for authors with the same name. As a result, researchers can extract relevant information from big data with scientific data, and obtain significant information based on cleansed and disambiguated data.


Visualization system Scientific data SOLR Implicit relationships 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jangwon Gim
    • 1
  • Yunji Jang
    • 1
  • Yeonghun Chae
    • 2
  • Hanmin Jung
    • 1
  • Do-Heon Jeong
    • 1
  1. 1.Korea Institute of Science and Technology InformationDaejeonSouth Korea
  2. 2.Korea UniversitySejongSouth Korea

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