Data-Ink Ratio

Data Ink Ratio

What Problem Does This Solve?

Improve the efficiency of communicating information by increasing the amount of relevant data.

Why Use This Pattern?

In a time when big data is omni-present, it becomes more and more important to edit and curate the data and its visualization. The American statistician Edward Tufte uses the term “Data-Ink Ratio” [1] to argue against using excessive decoration in visual displays of quantitative information. He states that an effective graph should aim to maximize the data-ink ratio, i.e. that a large share of “ink” (pixels) on a map should present data-information and therefore show more data that is relevant to the user performing a task.

Analogous to the map, a similar principle exists for human-computer interaction and is called signal-to-noise ratio. It represents the ratio of relevant to irrelevant information [2]. Anything that a user must process counts as either signal or noise, a well-designed app aims for a high signal-to-noise ratio.

When to Use This Pattern

As a basic rule, apply the Data-Ink Ratio to any map that is part of an app. There are two apps that require special attention to this principle though. Firstly, maps on mobile apps that have limited space to paint relevant information. Any noise on a small screen will over proportionally decrement usability. Secondly, single purpose apps that are aimed at people with less GIS experience and little time and patience to work through their task. The map as well as the interface components must be built with minimum distraction and “chart chunk”.

What’s the Solution?

Always strive to show what is important while simultaneously removing what is not important. Focus to show data and erase non-data ink and redundant-data ink.

To increase the data-ink ratio the author of a map must increase the amount of data points with value (data-ink) and decrease the content that is not necessary to comprehend the information represented (total ink used). The following techniques help to increase this ratio:

  • Chose the right basemap layer, go with the simplest option possible for the task on hand
  • Remove, hide, and dim layers
  • Show labels wisely; be selective, only show when necessary and consider scale-dependent labels
  • Follow cartographic rules
  • Guide users to their area of interest
  • Use patterns like Placemarks or Search

Special Considerations

Editing data is difficult and anticipating the multitude of display options might be overwhelming, but every time a user is confused, it adds friction and reduces trust which eventually will lead to abandoning the task and maybe even the application. The goal is reached when users don’t realize anymore that they are working with a map, when the map and its content become “invisible” to them.
Start by asking “What is the minimum set of visuals necessary to communicate the information understandably?” and continue by asking “Which elements (layers, features, labels, ornaments) can be removed without degrading the essence of what needs to be communicated?”

References

[1] The Visual Display of Quantitative Information; Tufte, E.; 1983; https://www.edwardtufte.com/tufte/books_vdqi (accessible: 11/4/2020)

[2] Signal-to-Noise Ratio; Chen, X.; September 9, 2018; https://www.nngroup.com/articles/signal-noise-ratio/ (accessible: 11/4/2020)

Examples

Canada is not relevant to the US-centric map but still uses most of the ‘ink’

Canada is not relevant to the US-centric map but still uses most of the ‘ink’

Leave a Reply