Select any example of a visualization or infographic, maybe your own work or that of others. The task is to undertake a deep, detailed ?

Select any example of a visualization or infographic, maybe your own work or that of others. The task is to undertake a deep, detailed ‘forensic’ like assessment of the design choices made across each of the five layers of the chosen visualization’s anatomy. In each case your assessment is only concerned with one design layer at a time.For this task, take a close look at the annotation choices:

Introduction

Visualizations are a complex design space with many different approaches. In this example, we’re looking at five different layers of a visualization: labels and legends, data encoding (e.g., color), axes and datum lines, focus and context. Each layer should be assessed independently so that you can evaluate each choice made in isolation from the others before moving on to the next one in turn.

Layer 1a: Labels, legends, and titles. Why have these been chosen? Are there better choices to be made in the case of labels and legends? In the case of title what is its role here?

Labels and legends are used to help the reader understand the data.

Titles should be descriptive, but not too long. They’re often placed above or below a visualization and they needn’t explain everything about it—they can be short and sweet if you want them to serve as only an intro for your readership.

You may have noticed that in most cases of this kind there are several layers within each graphic design element (e.g., labels), so try looking at each individual layer individually before moving on to other parts of your assessment process later down the line

Layer 1b: Data and encoding. What data values are being encoded through color, shape or size? What encoding choices have been made? What are their advantages and disadvantages?

Color is one of the most common ways to encode data values. In this layer, you should think about what kinds of information are being encoded by color and how it can be used in different ways depending on the type of data and type of visualization. For example, if we look at a map that shows environmental pollution data on an area level (elevation), then color will be used as a way to indicate whether an area has been polluted or not—and only one value per pixel matters here: red means high levels; green means low levels; blue means no data available yet because there hasn’t been enough time since measurement was taken last year etc…

Layer 2: Next consider the axes and datum lines. How are they situated on the visualization plane so that they achieve an appropriate balance between inclusion, exclusion, visibility and invisibility? Why have the chosen axes scales been chosen?

In this layer, you should consider the axes and datum lines. How are they situated on the visualization plane so that they achieve an appropriate balance between inclusion, exclusion, visibility and invisibility? Why have the chosen axes scales been chosen?

Axes are important to any visualization because they can be used to show relationships between data points (e.g., how much money spent by each department), or scale of data (e.g., showing how many cars were sold in a year). They should also be chosen carefully because they can influence how people interpret information from them; for example, if there are many small graphs on one page it may appear cluttered rather than organised when compared against other graphs which have been spaced out evenly across multiple pages or spread across several different documents/webpages but still managed nicely by using standardised spacing guides like 10mm margins around all edges of each graph so nothing overlaps unnecessarily while still allowing enough room around each text block within which we want them shown clearly without having too much surrounding space wasted away which could potentially result in confusion by readers who might not understand why certain items are included here versus others elsewhere (this would happen if someone were running multiple copies simultaneously).

Layer 3: Focus and context. What are the spatial relationships that exist within the context of the visualization’s visual frame versus those that exist outside it? How does this influence (or not) your ability to follow data of interest with regard to focus and context? How well do strategies such as isolating visual elements (e.g., via depth effects), using highlighting (e.g., color or shape cues), adding lines to connect data points across different contextual elements (e.g., using time-series charts) work here?

There are five layers of a visualization’s anatomy: content, design, data, code and presentation. The third layer is Focus and Context.

What are the spatial relationships that exist within the context of the visualization’s visual frame versus those that exist outside it? How does this influence (or not) your ability to follow data of interest with regard to focus and context? How well do strategies such as isolating visual elements (e.g., via depth effects), using highlighting (e.g., color or shape cues), adding lines to connect data points across different contextual elements (e.g., using time-series charts) work here?

Conclusion

The goal of this exercise is to take a close look at the design choices that have been made across each of the five layers of the chosen visualization’s anatomy. In each case your assessment is only concerned with one design layer at a time. For example: