Representation of bodily measurement of one species


What is the best way to represent the bodily measurement of only one species? For example I have this data:

Measurements (in mm). Male (n = 1) Body length, clypeus–apex of membrane: 12.49; head length: 2.00; head width, including compound eyes: 1.19; vertex width: 0.50; interocular width: 0.34; compound eye width: 0.35; anterocular length: 0.43; 1stantennal segment length: 6.25; 2nd antennal segment length: 2.31; 3rd antennal segment length: 4.48; 4th antennal segment length: 2.33; total antennal length: 15.07; 2nd rostral segment length: 1.01; 3rd rostral segment length: 0.61; 4th rostral segment length: 0.31; mesal pronotal length: 2.00; basal pronotal maximal width (excluding protuberance, straight): 1.92; anterior scutellumal width: 0.97; mesal scutellumal length: 1.05; maximal length across hemelytron: 8.60; maximal width across hemelytron: 1.95; foreleg (femur: tibia: tarsus): 4.66:4.40:0.32; midleg (femur: tibia: tarsus): 3.97:4.46:0.28; hindleg (femur: tibia: tarsus): 5.37:7.21:0.35.”

In some cases this list is much longer. I know about simple tabular representation, illustrative diagrams. With long list tabular might not be a good representative. What other solutions can one use?

Hi, Pawan,

This depends on the tasks that your visualization is intended to support. There is a common myth that visualization is for retrieving data values. In fact, in most cases, visualization provides poor support to accurate data retrieval (e.g., [1]). I guess that the tasks that you may wish to support may include (a) comparison between different species, (b) comparison between different instances within a species, or (c ) overview of many instances as part of a process of overview first and details on demand. For (a), the variations are expected to be large, and you may consider the approach by Duffy et al. [2]. For (b) and (c ), it is better to create a set of reference values (e.g., the mean values for a species), and you may consider to encode the values of an instance by juxtaposing them with (or relative to) the reference values. This allows viewers to notice the offsets quickly, or to compare different instances in terms of their offsets against the reference values.

[1] R. Kanjanabose, et al. A multi-task comparative study on scatter plots and parallel coordinates plots, Computer Graphics Forum, Wiley, 34(3):261-270, 2015.

[2] B. Duffy, et al. Glyph-based video visualization for semen analysis, IEEE Transactions on Visualization and Computer Graphics, 21(8):980-993, 2015.

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