I am studying the role of visualisation in UX and how it helps users understand content in a easy and quicker way. Does someone know of any studies that support visualisations at a cognitive level?
First picky point: Infographics aren't the same as visualisations. https://eagereyes.org/blog/2010/the-difference-between-infographics-and-visualization
The point of visualisation is to shift processing from the cognitive to the perceptual - i.e. don't think about it, just see it. There's hundreds of papers that compare different visualisations in user studies, generally such testing consisting of measuring and comparing task completion times and accuracy, with questionnaire-based tools as well to measure task load / ease etc (NASA-TLX etc). Bear in mind it's not always the case Vis A > Vis B, it also depends on the task being attempted. You just have to hit google scholar and if you find a review article all the better
As an example of a comparative study that uses NASA-TLX (no link to authors): Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation http://web.stanford.edu/~natalya/papers/iswc2013_tree_graph.pdf
It sounds like your question is two-fold. Here's my refinement: "What are best practices for data visualization to optimize for memorability and comprehension?"
In short, the two are at odds. Complexity and visual noise typically make data visualizations more memorable but less comprehensible. I've included a more thorough breakdown below.
- Faces and human-centric scenes are typically easy to remember 1
- Landscapes are not easy to remember 2
- Incorporation of a human-recognizable object (eg. photograph, people, cartoons, logos) makes visualizations more memorable 3
- Visual density improves memorability 3, 4
Visualizations are less memorable than natural scenes, but similar to images of faces, which may hint at generic, abstract, features of human memory 4
- Visualizations with low data-to-ink ratios and high visual densities (i.e., more chart junk and “clutter”) were more memorable than minimal, “clean” visualizations 4
- Unique visualization types (pictorial, grid/matrix, trees and networks, and diagrams) had significantly higher memorability scores than common graphs (circles, area, points, bars, and lines) 4
- Encapsulating visualizations in stories improves comprehension due to emotion, visceral, and visual associations 5
- Choosing the correct visualization type improves comprehension 6
- Using a single pre-attentive attribute (form, color, position, motion) improves comprehension 7
The simplest representation is most comprehensible 7
What Makes Data Visualization Memorable (Harvard)