Summary

For this week’s lecture, it is a continuation of last weeks pod which delves into the use cases of data visualisation through history while this week conveys more reasons into visualising data and modern examples. Firstly, Visualising is used to help users from having to go through multiple line of data and figuring out their meaning themselves which in turn saves time. An example of making data clearer to understand can be seen in the images below of country birth-rates which transforms from a table to a graph.

Table and graph

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Waterson, S. (2016). Visualisation: Historical and contemporary visualisation methods- part 2. 102269 Data visualisation. [Video file]. Retrieved from https://vimeo.com/176255825

Even though visualising can help in understanding data, too much of it can also make it more difficult to figure out which are called infographics.

Infographic

Reflection

The important aspect to get out of this lecture is that data visualising needs to be balanced in a way where there is not too much data to comprehend and not too much visualising of the data, which could distract the user from the information.

Summary

In this weeks lecture pod we learn about the purpose of data visualisation and the historical uses of them. The purpose of visualising data is to make it easier and quicker for more viewers to understand what is happening. In addition, this can be used to help viewers compare and contrast data to then be used to help make decisions for important matters at hand. An example of data visualisation use can be seen during times of war throughout history such as the graph below of Napoleons army fighting with Russia and the amount of death which occurred.

Reflection

I think the most important aspect of this video is the importance of data visualisation as it can help you in bringing forward solid arguments and choices depending on the visuals used to convey the data and the purpose of it.

Summary

In this week’s lecture pod, we go through the different types of measurements in data visualisation. The types are:

Nominal – Uses named categories which are inherently unordered. These are used to count and calculate percentages of each product while not being able to find the average between each of them separately.

Ordinal – Numbers in an order for example 1 to 5, and can be used to count and calculate percent’s but has trouble finding the average.

Interval – Is a numeric measurement from one point to another like time, temperature and calendars.

Ratio – Measures with numeric values and finds meaning from them and example of ratio data are height, weight and age.

Reflection

From watching the lecture I found that all these type of data measurement can all be useful as they each have their use cases but I believe they are best as shown in the pod when they used together to form a better understandable visualising of data.

Summary

In this weeks lecture pod we learn about Data and data visualisation and what they are. Data can be thought as the measurement of information and knowledge which have been obtained and interpreted. Data Visualisation is simply making data more easily comprehensible and usable through organisation and visual means such as graphs to be presented to the users.

Example of Data Visualisation from the lecture

Reflection

What I think is the most important aspect of the lecture pod is conveying the importance of visualising data as it helps users who gather the knowledge have a clearer understanding and scope of their statistics.

4×4 Model