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Summary on visualisation
Topic: Visualisation
by Elaine, 2018 Cohort
Note: This entry was created in 2018, when the task was to “summarise a key reading”, and so may not represent a good example to model current primer entries on.
Visualisation is a process of presenting data in a manner that makes it more accessible for its intended audience. Decision on the display technique is usually linked to the size of the complex problem, this meaning that the more number of actors and relations that exist within the problem, the more complex it is. Approaches to visualizing a complex problem should take in consideration its characteristics and the nature of information it displays, in order to identity the key players and roles within the problem. There is no one technique that is best for displaying the data under all circumstances. The purpose of this process is to communicate in a balanced manner the important features of the data but also taking into account what the perceiver should be learning or seeing in the display that is created.
One form of presentation would be statistical graphs. Well done statistical graphs consists of complex ideas communicated with clarity and precision. Some common features in these graphs should be that they,
- Show the data
- Reveal the data at several levels of detail
- Be integrated with verbal/clear written descriptions
- Serve a clear purpose overall; to illustrate the information the data
intend to portray
Example 1
Data map (death rates from cancer recorded in all counties in America, 1905- 1969)
The darker the colour of the area shown, the higher rates of death from cancer in that region.
In this type of display, the data maps can provide many leads to the causes, and avoidance of cancer through the evaluation of the environment of that region to identity factors that could have exacerbated the statistics.
Example 2 Time-series plot
The time-series plot records changes in data over time, by plotting the graph with changes in seconds, minutes, hours, days, week, months, years, centuries and so on. They are best used for when presenting big data sets with variability.
A popular topic displayed with these kind of maps would be the history and genealogy of royalty. Below is an example of E.J. Mareys plot of a series of English rulers that conveys a sense of march of history.
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This content has been contributed by a student as part of a learning activity.
If there are inaccuracies, or opportunities for significant improvement on this topic, feedback is welcome on how to improve the resource.
You can improve articles on this topic as a student in "Unravelling Complexity", or by including the amendments in an email to: Chris.Browne@anu.edu.au
Note: This entry was created in 2018, when the task was to “summarise a key reading”, and so may not represent a good example to model current primer entries on.
Visualisation is a process of presenting data in a manner that makes it more accessible for its intended audience. Decision on the display technique is usually linked to the size of the complex problem, this meaning that the more number of actors and relations that exist within the problem, the more complex it is. Approaches to visualizing a complex problem should take in consideration its characteristics and the nature of information it displays, in order to identity the key players and roles within the problem. There is no one technique that is best for displaying the data under all circumstances. The purpose of this process is to communicate in a balanced manner the important features of the data but also taking into account what the perceiver should be learning or seeing in the display that is created.
One form of presentation would be statistical graphs. Well done statistical graphs consists of complex ideas communicated with clarity and precision. Some common features in these graphs should be that they,
- Show the data
- Reveal the data at several levels of detail
- Be integrated with verbal/clear written descriptions
- Serve a clear purpose overall; to illustrate the information the data
intend to portray
Example 1
Data map (death rates from cancer recorded in all counties in America, 1905- 1969)
The darker the colour of the area shown, the higher rates of death from cancer in that region.
In this type of display, the data maps can provide many leads to the causes, and avoidance of cancer through the evaluation of the environment of that region to identity factors that could have exacerbated the statistics.
Example 2 Time-series plot
The time-series plot records changes in data over time, by plotting the graph with changes in seconds, minutes, hours, days, week, months, years, centuries and so on. They are best used for when presenting big data sets with variability.
A popular topic displayed with these kind of maps would be the history and genealogy of royalty. Below is an example of E.J. Mareys plot of a series of English rulers that conveys a sense of march of history.