Visualisation: Historical and contemporary visualisation methods-Part 1

Part 1:Screen Shot 2016-08-03 at 11.03.27 AM.png
Napoleon’s Invasion of Russia 1812. (painting)

Screen Shot 2016-08-03 at 11.05.30 AM.png Created by french engineer in the 60’s. (map)

  • polish border (left) and moscow border (right).
  • shows the loss of men from left to right and right to left through the thickness of the lines.
  • Temperature is also shown by vertical lines.
  • Reduces the time to understand the data.

 

Screen Shot 2016-08-03 at 11.09.42 AM.png

South of Ukraine (Crimean) 

  • War between Russia and England.
  • 6 Months to get access to medicine.
  • Soldiers were dying and wanted to improve the lives of soldiers.

Screen Shot 2016-08-03 at 11.12.02 AM.png

  • Graphing the causes of death during the war.
  • The real threat was disease to the soldiers.
  • Shows comparison of two years for each graph.
  • Made through area, the smaller numbers in the middle to at least be visible.
  • Visually show the impact over a period of time.

 

Screen Shot 2016-08-03 at 11.28.43 AM.png
Poster for an exhibition.

  • Make issues understandable for the uneducated through visual education.
  • Popularised multiples of something to equal something greater.
  • Bringing the museum to the people, to distribute ideas.

Screen Shot 2016-08-03 at 11.33.03 AM.png

Using visual education to transform the masses.

Part 2:

Why visualise?

Help us understand complex data and see the trends that are not able to be seen with lots of numbers. Through the use visuals the understanding is made clearer and faster.

Screen Shot 2016-08-09 at 1.51.58 PM.png(Visualised: data has been plotted into a graph making it clear to the viewer about what the data is saying .)

Screen Shot 2016-08-09 at 1.52.09 PM.png(Raw data: too much information for the viewer to decode)

Screen Shot 2016-08-09 at 1.54.18 PM.png
(Useless visualisation when the software export the data into a graph.)

  • Use visualisations to convince the audience of the message or claim the data is making.
  • Let the audience extract their own meaning.

 

 

 

 

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