83 lines
2.3 KiB
Markdown
83 lines
2.3 KiB
Markdown
# The Value of Visualisation
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###### Why create a Visualisation?
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- Answer questions (or discover them)
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- Make decisions
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- See data in context
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- Expand memory
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- Support graphical calculation
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- Find patterns and trends
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- Present arguments or tell a story
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> A picture is worth a 1000 words
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**Record** information
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- Blueprints, photographs, seismographs
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**Communicate** information to others
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- Share and persuade
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- Think of Florence Nightingale using a graph to show that infection was the leading cause of death in hospitals
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- Collaborate and revise
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- Think of the London tube map: before it was geographically accurate, now it is only topologically accurate
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Analyse data to **support reasoning**
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- Find patterns
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- Think of the London Cholera map, how John Snow found out where the infection was coming from
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- Discover errors in data
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- Expand memory
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- Imagine doing a sum like $34\times 52$ mentally versus with a pen and paper
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- Visualising the sum (column multiplication) can expand your memory
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- Develop and assess hypotheses
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#### Different Stages of Visualisation
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- Data transformation
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- Create a structural model, schema, mapping raw data into data tables
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- Visual Mapping
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- Create a visual spatial model, transforming data tables into visual structures
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- View Transformations
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- Create views of the Visual Structures by specifying graphical parameters such as position, scaling and clipping.
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###### Acquire
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- Obtain the data, whether from a file on a disk or network
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###### Parse
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- Provide some structure for the data’s meaning, and order it into categories
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###### Filter
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- Remove all but interesting data
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###### Mine
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- Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context
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- Work out mean, standard deviation etc
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###### Represent
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- Choose a visual model
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- Bar chart, graph, pie chart etc
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###### Refine
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- Improve the basic representation to make it clearer and more engaging
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###### Interact
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- Add methods for manipulating the data or controlling what features are visible
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##### Interaction is Vital for Exploration
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- Engage in a dialogue with your data
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- Employ interaction in a more fundamental manner to strengthen the power of visualisation
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