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docs/lectures/infovis/02_value_of_visualisation.md

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+# The Value of Visualisation
+
+###### Why create a Visualisation?
+
+- Answer questions (or discover them)
+- Make decisions
+- See data in context
+- Expand memory
+- Support graphical calculation
+- Find patterns and trends
+- Present arguments or tell a story
+
+> A picture is worth a 1000 words
+
+**Record** information
+
+- Blueprints, photographs, seimographs
+
+**Communicate** information to others
+
+- Share and persuade
+  - Think Florence Nightingale using a graph to show deaths to infection was the leading cause of death in hospitals
+- Collaborate and revise
+  - Think the London tube map, before was geographically accurate, now is only topologically accurate
+
+Analysis data to **support reasoning**
+
+- Find patterns
+  - Think the London Cholera map, how John Snow found out where the infection was coming from
+- Discover errors in data
+- Expand memory
+  - Imaging doing a sum like $34\times 52$ mentally verses with a pen and paper
+  - Visualising the sum (column multiplication) can expand your memory
+- Develop and assess hypotheses
+
+#### Different Stages of Visualisation
+
+![1645033524.png](img/1645033524.png)
+
+- Data transformation
+  - Create a structural model, schema, mapping raw data into data tables
+- Visual Mapping
+  - Create a visual spatial model, transforming data tables into visual structures
+- View Transformations
+  - Create views of the Visual Structures by specifying graphical parameters such as position, scaling and clipping.
+
+![1645033689.png](img/1645033689.png)
+
+###### Acquire
+
+- Obtain the data, whether from a file on a disk or network
+
+###### Parse
+
+- Provide some structure for the data’s meaning, and order it into categories
+
+###### Filter
+
+- Remove all but interesting data
+
+###### Mine
+
+- Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context
+  - Work out mean, standard deviation etc
+
+###### Represent
+
+- Choose a visual model 
+  - Bar chart, graph, pie chart etc
+
+###### Refine
+
+- Improve the basic representation to make it clearer and more engaging
+
+###### Interact
+
+- Add methods for manipulating the data or controlling what features are visible
+
+##### Interaction is Vital for Exploration
+
+- Engage in a dialog with your data
+- Employ interaction in a more fundamental manner to strengthen the power of visualisation
+