11 Unit 2
Learning Elements
In this unit, we will cover how to visualise network data. Throughout, I encourage your to think about two main purposes of data visualisation that extend to working with networks. One is for you, the data scientist, and the other is for your constituents. Visualisations can tell you more about your data. On the one hand, you may learn that you need to do some more cleaning (self loops, extraneous nodes etc.) as you visualise your data. Doing so can drive questions that need answering about this group. For example, seeing that there are a few highly central figures in the network may push you to ask questions about those individuals. On the other hand, the visuals you create should engage stakeholders and tell the story of your analysis. So, visualisation is both an exploratory tool for you and a communication tool for the viewer. In this unit, then, you will learn tools to help you and your audience fully appreciate the stories that are in your network!
By the end of this unit you will:
Produce basic (clean), intermediate (storytelling), and more advanced (engaging) visualisations.
Understand that visuals are more than just eye catchers, they are storytellers.
Learn about visual accessibility.
Project Milestones
| Milestone (assignments linked) | Explanation |
|---|---|
| Data Exploration | Students will give descriptions of the network data they are using. They will discuss possible transformations to the data that they will need to perform before analysing. They may also provide basic visualisations to demonstrate this. |
| Visualisations | Students will provide multiple visualisations of the network they are studying. This assignment requires students to demonstrate they have learned how to make basic visualization, clean visualization, and more advanced visualisations (i.e. at least one dynamic or interactive version of their network). |
Workforce Preparation
Visualisaion can be an effective form of communication. It can also confuse, if not done well. It is up to you to ensure the audience interprets your visualisations the way you intend. Network data may not be the most intuitive depictions of data for people. While their novelty make for an attractive visualisation, people are not as used to interpreting them as they are other charts or graphs because network analysis is more novel. Be mindful of their readability and clarity. Just because you know what is going on, others may not find things so comprehensible. The correct use of space, colours, and labels can draw people’s attention to what you are trying to portray. Keep these at the front of your mind as we go through these next few chapters.
Enjoy Unit 2!