Lecture Notes

Lecture One

PART 1: What is Data Visualisation?

Data visualisation is the visualising of information so that patterns and connections can be inferred. It is the process of designing information so that it makes a lot more sense, tells a story, or allows one to focus only on the important aspects of the information.

Data visualisation is viewed by many disciplines as a modern equivalent of visual communication. It involves the creation and study of the visual representation of data.

“Information that has been abstracted in some schematic form, including attributes or variables for the units of information.” Michael Friendly (2008)

Data visualisation is one of the steps in analysing data and presenting it to users. A primary goal of visualisation is to communicate information clearly and efficiently using statistical graphics, plots and information graphics.

Data visualisation is a fundamental part within the communication system. Examples of data visualisation can include the following:

  • Dynamic weather maps
  • Virtual heritage
  • Epidemiology
  • Tracking polluted water
  • Patterned recognition and health data
  • Complex crimes – corporate laws

The amount of data within the world is growing extensively and on an individual level, we consume an incredible amount each day through social media, banking, television, etc.

“There is a tsunami of data that is crashing onto the beaches of the civilised world… Coming in an unorganised, uncontrolled, incoherent cacophony of foam. None of it is easily related, none of it comes with any organisation methodology.” – Richard Saul Wurman in Information Architects

Wurman, R. S (1997) Information Architects, Graphis Inc; USA

Role of the Designer

We need to be able to organise and better represent the growing scope of data in order to clearly understand its meaning.
Designers engage with the aesthetics, forms and the politics of data presentation.

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What is Data?

Data is the values of quantities collected together for reference or analysis. It can be visualised through graphs and images in order to better understand it.

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  • Data is the lowest layer of extraction.
  • Visualisation, or the presentation layer is the next level that leads to information, and finally, knowledge is the story telling or the conversation around a presentation.
  • Data on itself carries no meaning. For data to become information, it needs to be interpreted and take on a meaning.

Difference between information graphics and data visualisation?

Not all information visualisations are based on data, but all data visualisations are information visualisations.
In more simpler terms, informations are the visualisation of words, content and assumptions, whereas data visualisation is the visualisation of numbers and statistics.

infographics-process_509e119959153_w1500

The above example is not a data visualisation – it is just a list with images.

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The above example is also not data visualisation, but it looks like one. There’s not too much information provided and is an example of making something look meaningful.

Effective visualisation helps users to analyse and reason the data and it’s evidence. It makes complex data more accessible, understandable and usable.

The above bar chart is the best form of data visualisation because there are have two different variables being compared.

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http://www.bbc.co.uk/bitesize/ks3/maths/handling_data/representing_data/revision/3/

The above example is a line chart, which is when information is being compared over a certain period of time.

PART 2: The 4×4 model for winning knowledge content online

It has been shown through studies that most users who visit a site, won’t stay on there for too long. If they do not show immediate interest in the site, in terms of the design and the content, they will leave it within about 10 seconds. While there are visitors who stay on the site for longer than the ten seconds, they will only briefly skim it, without actually having a thorough read of the content. This is done in what is known as an “F pattern”, as shown in Fig 1. They will keep doing this until they find something on the site that they are drawn to, and care about.

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Fig 1. https://www.nngroup.com/articles/f-shaped-pattern-reading-web-content/

While this is a major issue, there is a simple solution called the “4×4 Model for Knowledge Content” which consists of four key models and four critical components of those models:

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http://inspiredm.com/winning-knowledge-content/

1) The Water Cooler

  • This content is succinct, direct and compelling
  • It includes the fundamental components of a page such as the headline, a tweet or an advertisement
  • The Water Cooler is the first component that users look at when viewing a site. It will determine whether they are interested enough to explore the other components of the site, such as the content. Therefore, the Water Cooler needs to engage with users and grab their attention.

2) The Research Library

  • The library is where one goes to really learn about and dig deeper into a certain topic of interest.
  • You go to the library to really learn about a topic. It is where all the research and data is contained which backs up the Water Cooler and the Cafe (colleagues). It is the scholarly, long form of content.
  • The Water Cooler moments however, should not go away – they should still remain present while the library is being explored. It is important to note that it is more likely for a text to be read by its audience if it is broken up into different sections containing not only text itself, but images, data visualisations, as well as the callouts.

3) The Lab

  • The lab is where users can interact with the data found in the Research Library. This is the rarest form of content but, in many ways, it’s the most powerful. If you choose data and bubble it up to a headline, you’re making a thousand editorial decisions.
  • Water Cooler moments are all agenda-driven. Café moments slightly less so, library moments even less. However, even in the research library, the data has been massaged and analyzed and delivered in a package. In the lab, you open the vaults and give users access to the data. They can twist the knobs and make it about them and their interests.
  • In addition to our four models of content, we have four critical components that should be used throughout the models. The arguments for them are many, but the key idea is that these elements all increase understanding, engagement, retention and social sharing. This will lead to better outcomes for your users and, therefore, for you.

COMPONENTS:

1) Visualisation
Consider a bar chart compared to a table of data in Excel. Which one is understandable within that all-important 10 seconds? Which tells a story? Visualization is not just about data, but also concept and geographic visualization.

2) Story-telling
Explaining a concept is nothing like weaving a narrative. If you can tell a story, you are able to convert the abstract into something people can relate to. Liberal use of video is an effective story-telling and visualization tool and we recommend it highly, but it’s not the only way.

3) Interactivity
If I can see something, I can understand it. If I can touch it, I can know it. Why is the web a successful and popular medium? It’s not just that it’s convenient. It’s also that it allows us to be the masters of our own destiny. I don’t have to wait for the Boston Globe to land on my doorstep and read what they chose to write. I’m free to explore online and find my own content. This does NOT mean over-using hyperlinks. It has been shown that understanding decreases when you add too many hyperlinks within content. But it does mean offering interactive experiences such as Lab moments and/or images that can be zoomed for more detail and/or communities to engage in.

4) Shareability
How easy is it to share a full research report and for the recipient to consume that report? Compare that to sharing/consuming one data point or one quote. The power of water cooler moments is strongest when you think about sharing. Those are the nuggets most likely to be shared by your audience – leading more traffic back to all levels of your site content. Oh, and you have to have the basic sharing tools so it’s easy (Tweet and Like buttons, for instance).

The 4X4 approach is the secret to presenting knowledge content in a way that engages your audience, stepping them into the right level of content based on their needs, and improving outcomes from that content. Try 4X4 and you won’t go back to a rear-wheel-drive approach ever again!

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