A Novel Metaphor Graph Drawing Method for Multidimensional Data Visualisation and Its Case Study on COVID-19...

Area of Science:

• Data Visualization
• Information Design
• Scientific Data Analysis

Background:

• Multidimensional data visualization techniques face limitations including inaccurate comparisons, perception issues, and visual clutter.
• Existing methods often fail to fully represent complex datasets or link multiple attributes efficiently.

Purpose of the Study:

• To propose and evaluate a novel graphical drawing method, the multidimensional rose chart, designed to overcome limitations of existing multidimensional data visualization techniques.
• To enhance the representation and comparison of multidimensional data through an improved graphical approach.

Main Methods:

• Developed a novel multidimensional rose chart inspired by the Nightingale rose chart, incorporating color shades, area, and height for value representation.
• Utilized graph nesting for straightforward attribute comparison and specific value labels for detailed attribute display.
• Validated the method using COVID-19 data, comparing it against traditional methods like line charts, bar charts, and parallel coordinate charts.

Main Results:

• The multidimensional rose chart demonstrated effectiveness in presenting multidimensional data compared to traditional methods.
• Experimental results showed the method's ability to enrich data representation and facilitate attribute comparisons.
• The findings align with existing research conclusions in COVID-19 data analysis sectors.

Conclusions:

• The multidimensional rose chart offers a promising supplemental approach for multidimensional data analysis.
• The novel method effectively addresses challenges related to incomplete data presentation, attribute linkage, and interface simplicity.
• This visualization technique has the potential to improve data understanding and comparison in various scientific fields.