Archive for the ‘Perception’ Category

No Perception Without Cartography [Failure To Communicate As Cartographic Failure]

Saturday, April 9th, 2016

Dan Klyn tweeted:

No perception without cartography

with an image of this text (from Self comes to mind: constructing the conscious mind by Antonio R Damasio):


The nonverbal kinds of images are those that help you display mentally the concepts that correspond to words. The feelings that make up the background of each mental instant and that largely signify aspects of the body state are images as well. Perception, in whatever sensory modality, is the result of the brain’s cartographic skill.

Images represent physical properties of entities and their spatial and temporal relationships, as well as their actions. Some images, which probably result from the brain’s making maps of itself making maps, are actually quite abstract. They describe patterns of occurrence of objects in time and space, the spatial relationships and movement of objects in terms of velocity and trajectory, and so forth.

Dan’s tweet spurred me to think that our failures to communicate to others could be described as cartographic failures.

If we use a term that is unknown to the average reader, say “daat,” the reader lacks a mental mapping that enables interpretation of that term.

Even if you know the term, it doesn’t stand in isolation in your mind. It fits into a number of maps, some of which you may be able to articulate and very possibly into other maps, which remain beyond your (and our) ken.

Not that this is a light going off experience for you or me but perhaps the cartographic imagery may be helpful in illustrating both the value and the risks of topic maps.

The value of topic maps is spoken of often but the risks of topic maps rarely get equal press.

How would topic maps be risky?

Well, consider the average spreadsheet using in a business setting.

Felienne Hermans in Spreadsheets: The Ununderstood Dark Matter of IT makes a persuasive case that spreadsheets are on an average five years old with little or no documentation.

If those spreadsheets remain undocumented, both users and auditors are equally stymied by their ignorance, a cartographic failure that leaves both wondering what must have been meant by columns and operations in the spreadsheet.

To the extent that a topic map or other disclosure mechanism preserves and/or restores the cartography that enables interpretation of the spreadsheet, suddenly staff are no longer plausibly ignorant of the purpose or consequences of using the spreadsheet.

Facile explanations that change from audit to audit are no longer possible. Auditors are chargeable with consistent auditing from one audit to another.

Does it sound like there is going to be a rush to use topic maps or other mechanisms to make spreadsheets transparent?

Still, transparency that befalls one could well benefit another.

Or to paraphrase King David (2 Samuel 11:25):

Don’t concern yourself about this. In business, transparency falls on first one and then another.

Ready to inflict transparency on others?

How to design better data visualisations

Tuesday, October 15th, 2013

How to design better data visualisations by Graham Odds.

From the post:

Over the last couple of centuries, data visualisation has developed to the point where it is in everyday use across all walks of life. Many recognise it as an effective tool for both storytelling and analysis, overcoming most language and educational barriers. But why is this? How are abstract shapes and colours often able to communicate large amounts of data more effectively than a table of numbers or paragraphs of text? An understanding of human perception will not only answer this question, but will also provide clear guidance and tools for improving the design of your own visualisations.

In order to understand how we are able to interpret data visualisations so effectively, we must start by examining the basics of how we perceive and process information, in particular visual information.

Graham pushes all of my buttons by covering:

A reading list from this post would take months to read and years to fully digest.

No time like the present!

a Google example: preattentive attributes

Tuesday, October 15th, 2013

a Google example: preattentive attributes

From the post:

The topic of my short preso at the visual.ly meet up last week in Mountain View was preattentive attributes. I started by discussing exactly what preattentive attributes are (those aspects of a visual that our iconic memory picks up, like color, size, orientation, and placement on page) and how they can be used strategically in data visualization (for more on this, check out my last blog post). Next, I talked through a Google before-and-after example applying the lesson, which I’ll now share with you here.

Preattentive attributes.

Now there is a concept to work into interface/presentation design!

Would its opposite be:

Counter-intuitive attributes?

Are you using “preattentive attributes” in interfaces/presentations or do you rely on what you find intuitive/transparent?

I first saw this cited at Chart Porn.

The science behind data visualisation

Tuesday, October 15th, 2013

The science behind data visualisation

From the post:

Over the last couple of centuries, data visualisation has developed to the point where it is in everyday use across all walks of life. Many recognise it as an effective tool for both storytelling and analysis, overcoming most language and educational barriers. But why is this? How are abstract shapes and colours often able to communicate large amounts of data more effectively than a table of numbers or paragraphs of text? An understanding of human perception will not only answer this question, but will also provide clear guidance and tools for improving the design of your own visualisations.

In order to understand how we are able to interpret data visualisations so effectively, we must start by examining the basics of how we perceive and process information, in particular visual information.

A great summary of work on human perception of visualizations.

How you visualize data will impact how quickly (if at all) others “understand” the visualization and what conclusions they will draw from it.

One of the classic papers cited by the author is: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. William S. Cleveland; Robert McGill (PDF)

I first saw this at Chart Porn.