Last updated: Feb 29, 2020
In the last article, we learned about modeling data as a graph and how network modeling is particularly useful for mapping relationships. In this article, we'll explore what to do once you have modeled your data in a graph form.
Often, the most useful next step (after you have put your data in network form), is to visualize it. Why? Visualization helps you spot errors, it gives you a mental picture of your data, and it helps you make sense of any ensuing graph metrics. Visualization also helps your audience better connect with your data.
But first, before we discuss the details of making graph visualizations, let's discuss what tools are available to make them. Most tools require you to know how to code, but we'll give a run-down of three popular options:
Open-source, download required, coding required
GraphViz is one of the most established open-source graph visualization tools out there. It lets users generate graph diagrams from descriptions of graphs in a text-like language, and outputs diagrams in PNG or vector formats. The key factor here is that some setup and coding is required, as well as massaging of your data into the DOT language format. One of the distinguishing strengths of GraphViz lies in its mathematical prowess in graph layout — its authors have authored dozens of papers on efficient ways of implementing routers and drawing graphs. GraphViz is also highly-customizable due to its requirement that users write code. All in all, GraphViz has been around for a long time and is a solid choice for those who have the time to introduce a coding component to their research and process.
Pros: Free, mathematically-sophisticated layout algorithms
Open-source, download required
Much like GraphViz, Gephi is another download-required open-source graph visualization tool. Unlike GraphViz, no coding is required for Gephi, however, Gephi also requires you to download and install software on your computer. Depending on the size of your data, it requires different miniumum levels of memory to run quickly, and also has a Java dependency. Gephi is a good option f you are a researcher with hundreds of thousands of data points and don't need to be able to easily share and collaborate with others on graph visualization.
Pros: Open-source, highly-customizable
Free, 100% online, no coding
Since this article is by Rhumbl, we'll take the chance to contrast how Rhumbl is different from the other tools. Firstly, Rhumbl is 100% online, which means you don't need to worry about downloading or installing software. Secondly, the data spreadsheets that you import into Rhumbl is in an intuitive, easy-to-understand format. This means that you and collaborators can easily edit and reason about the data. Rhumbl also has the concept of groups – a visually-intuitive way to group nodes. Rhumbl is a good choice for those who need to make pretty and interactive graph visualizations without needing to code or write scripts to massage their data.
Pros: Free, user-first design, easy to import data format
For a more comprehensive list of tools for graph visualization, check out this Medium article.
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