Making Infographics in Canva: a Guide and Review

Introduction

If you’ve ever had to design a poster for class, you’re probably familiar with Canva. This online and app-based graphic design tool, with free and subscription-based versions, features a large selection of templates and stock graphics that make it pretty easy to create decent-looking infographics. While it is far from perfect, the ease of use makes Canva worth trying out if you want to add a bit of color and fun to your data presentation.

Getting Started

Starting with a blank document can be intimidating, especially for someone without any graphic design experience. Luckily, Canva has a bunch of templates to help you get started.

Canva infographic templates

I recommend picking a template based on the color scheme and general aesthetic. It’s unlikely you’ll find a template that looks exactly how you want, so you can think of a template as a selection of colors, fonts, and graphics to use in your design, rather than something to just copy and paste things into. For example, see the image below – I recently used the template on the left to create the infographic on the right.

An infographic template compared to the resulting infographic

General Design Principles

Before you get started on your infographic, it’s important to remember some general design guidelines:

  1. Contrast. High levels of contrast between your background and foreground help keep everything legible.
  2. Simplicity. Too many different colors and fonts can be an eyesore. Stick to no more than two fonts at a time.
  3. Space. Leave whitespace to keep things from looking cluttered.
  4. Alignment and balance. People generally enjoy looking at things that are lined up neatly and don’t have too much visual weight on one side or another.
An exaggerated example of a design that ignores the above advice.

Adding Graphs and Graphics

Now that you have a template in hand and graphic design principles in mind, you can start actually creating your infographic. Under “Elements,” Canva includes several types of basic charts. Once you’ve added a chart to your graphic, you can edit the data associated with the chart directly in the provided spreadsheet, by uploading a csv file, or by linking to a google spreadsheet.

Canva interface for creating charts

The settings tab allows you to decide whether you want the chart to include a legend or labels. The options bar at the top allows for further customization of colors and bar or dot appearance. Finally, adding a few simple graphics from Canva’s library such as shapes and icons can make your infographic more interesting. 

Examples of charts available in Canva, with a variety of customizations.

Limitations and Frustrations

The main downsides to Canva are the number of features locked behind a paywall and the inability to see only the free options. Elements cannot be filtered by price and it seems that more and more graphics are being claimed by Canva Pro, so searching for graphics can be frustrating. Templates can be filtered, but it will still bring up results where the template itself is free, but there are paid elements within the template. So, you might choose a template based on a graphic that you really like, only to find out that you need a Canva Pro subscription to include that graphic.

The charts in Canva also have limitations. Pie charts do not allow for the selection of colors for each individual slice; you have to pick one color, and Canva will generate the rest. However, if you want to have more control over your charts, or wish to include more complicated data representations, you can upload charts to Canva, which even supports transparency.

Conclusion

As mentioned above, Canva has its downsides. However, Canva’s templates, graphics, and charts still make it a super useful tool for creating infographics that are visually appealing. Try it out the next time you need to present some data!

Simple NetInt: A New Data Visualization Tool from Illinois Assistant Professor, Juan Salamanca

Juan Salamanca Ph.D, Assistant Professor in the School of Art and Design at the University of Illinois Urbana-Champaign recently created a new data visualization tool called Simple NetInt. Though developed from a tool he created a few years ago, this tool brings entirely new opportunities to digital scholarship! This week we had the chance to talk to Juan about this new tool in data visualization. Here’s what he said…

Simple NetInt is a JavaScript version of NetInt, a Java-based node-link visualization prototype designed to support the visual discovery of patterns across large dataset by displaying disjoint clusters of vertices that could be filtered, zoomed in or drilled down interactively. The visualization strategy used in Simple NetInt is to place clustered nodes in independent 3D spaces and draw links between nodes across multiple spaces. The result is a simple graphic user interface that enables visual depth as an intuitive dimension for data exploration.

Simple NetInt InterfaceCheck out the Simple NetInt tool here!

In collaboration with Professor Eric Benson, Salamanca tested a prototype of Simple NetInt with a dataset about academic publications, episodes, and story locations of the Sci-Fi TV series Firefly. The tool shows a network of research relationships between these three sets of entities similar to a citation map but on a timeline following the episodes chronology.

What inspired you to create this new tool?

This tool is an extension of a prototype I built five years ago for the visualization of financial transactions between bank clients. It is a software to visualize networks based on the representation of entities and their relationships and nodes and edges. This new version is used for the visualization of a totally different dataset:  scholarly work published in papers, episodes of a TV Series, and the narrative of the series itself. So, the network representation portrays relationships between journal articles, episode scripts, and fictional characters. I am also using it to design a large mural for the Siebel Center for Design.

What are your hopes for the future use of this project?

The final goal of this project is to develop an augmented reality visualization of networks to be used in the field of digital humanities. This proof of concept shows that scholars in the humanities come across datasets with different dimensional systems that might not be compatible across them. For instance, a timeline of scholarly publications may encompass 10 or 15 years, but the content of what is been discussed in that body of work may encompass centuries of history. Therefore, these two different temporal dimensions need to be represented in such a way that helps scholars in their interpretations. I believe that an immersive visualization may drive new questions for researchers or convey new findings to the public.

What were the major challenges that came with creating this tool?

The major challenge was to find a way to represent three different systems of coordinates in the same space. The tool has a universal space that contains relative subspaces for each dataset loaded. So, the nodes instantiated from each dataset are positioned in their own coordinate system, which could be a timeline, a position relative to a map, or just clusters by proximities. But the edges that connect nodes jump from one coordinate system to the other. This creates the idea of a system of nested spaces that works well with few subspaces, but I am still figuring out what is the most intuitive way to navigate larger multidimensional spaces.

What are your own research interests and how does this project support those?

My research focuses on understanding how designed artifacts affect the viscosity of social action. What I do is to investigate how the design of artifacts facilitates or hinders the cooperation of collaboration between people. I use visual analytics methods to conduct my research so the analysis of networks is an essential tool. I have built several custom-made tools for the observation of the interaction between people and things, and this is one of them.

If you would like to learn more about Simple NetInt you can find contact information for Professor Juan Salamanca here and more information on his research!

If you’re interested in learning more about data visualizations for your own projects, check out our guide on visualizing your data, attend a Savvy Researcher Workshop, Live Chat with us on Ask a Librarian, or send us an email. We are always happy to help!