PCNL: A Visual Analysis Method for Comparing Homogeneous Hierarchical Data

Authors

Dong Yu, Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;
Chen Yi, Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;
Yuehong Sun, Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;

Abstract

Abstract: According to the requirements of comparing homogeneous hierarchical data in different fields, a visual analysis method called PCNL is presented in this paper. Homogeneous information is extracted from the multiple levels of the heterogeneous hierarchical data set, and isomorphic node-link trees are constructed. Parallel coordinates are combined with node-link trees, which displays attribute values of leaf nodes in multiple isomorphic trees. Interactive techniques are introduced to help users to compare and analyze multiple attributes of each leaf node in multiplehomogeneous hierarchical structures. Applying this method to compare multi-national MRL data in food safety field can help users to analyze the general trend and detail difference of the multinational MRL effectively, and find out the existing problems of Chinese MRL standards.

Recommended Citation

Yu, Dong; Yi, Chen; and Sun, Yuehong (2020) "PCNL: A Visual Analysis Method for Comparing Homogeneous Hierarchical Data," Journal of System Simulation: Vol. 29: Iss. 11, Article 15.
DOI: 10.16182/j.issn1004731x.joss.201711015
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss11/15

First Page

2700

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201711015

Last Page

2708

CLC

TP391

Recommended Citation

Dong Yu, Chen Yi, Sun Yuehong. PCNL: A Visual Analysis Method for Comparing Homogeneous Hierarchical Data[J]. Journal of System Simulation, 2017, 29(11): 2700-2708.

DOI

10.16182/j.issn1004731x.joss.201711015