Visual Analysis on Macro Quality Data

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 787)


Quality inspection and quarantine processing is an important process with extensive business impacts. Data visualization methods failed to fully combine standards and certifications or accreditation. While inspection, quarantine and other quality related measures are hard to analyze due to the multi-factor dimension and therefore it is difficult to reflect the macro quality status. Thus, in order to integrate quality data from quality supervisory inspection and quarantine departments, this paper propose three visualization methods to analyze quality data, such as tree models and histogram visualization, map and histogram visualization, the models implement quality visualization system based on the methods above to realize the comprehensive analysis of macro quality data.


Data visualization Macro quality data Data analysis Time series visualization 



This paper is supported by grants from National Key R&D Program of China (2016YFF0204205) and China National Institute of Standardization (712016Y-4941-2016, 522016Y-4681-2016).


  1. 1.
    Friendly, M.: Milestones in the history of thematic cartography, statistical graphics, and data visualization (2008)Google Scholar
  2. 2.
    Wu, Y., Cao, N., Gotz, D., Tan, Y.P., Keim, D.: A survey on visual analytics of social media data. IEEE Trans. Multimed. 18, 2135–2148 (2016)CrossRefGoogle Scholar
  3. 3.
  4. 4.
    Smith, A., Hawes, T., Myers, M.: Hiearchie: visualization for hierarchical topic models. In: The Workshop on Interactive Language Learning, pp. 71–78 (2014)Google Scholar
  5. 5.
    Draper, G.M., Livnat, Y., Riesenfeld, R.F.: A survey of radial methods for information visualization. IEEE Trans. Vis. Comput. Graph. 15(5), 759–776 (2009)CrossRefGoogle Scholar
  6. 6.
    Coppola, A., Stewart, B.: A tool for structural topic model visualizations (2016)Google Scholar
  7. 7.
    Macro Quality Data.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.China National Institution of StandardizationBeijingChina
  2. 2.AQSIQ Key Laboratory of Human Factors and Ergonomics (CNIS)BeijingChina

Personalised recommendations