What are the best VR data visualization tools for your project?

1 Your data type and size

The first thing to consider is what kind of data you want to visualize and how big it is. Different types of data may require different methods and formats of visualization, such as charts, graphs, maps, networks, or 3D models. For example, if you want to visualize spatial or geographical data, you may need a tool that supports geo-referencing and terrain rendering. If you want to visualize network or relational data, you may need a tool that supports graph layout and node-link diagrams. The size of your data also matters, as some tools may have limitations or performance issues when dealing with large or dynamic data sets. You may need a tool that can handle streaming, filtering, or aggregating data, or that can leverage cloud computing or distributed processing.

2 Your VR platform and hardware

The next thing to consider is what VR platform and hardware you will use to create and view your VR data visualization. There are many VR platforms and devices available, such as Oculus, HTC Vive, Windows Mixed Reality, or WebVR. Each platform may have different features, capabilities, and requirements for developing and deploying VR applications. You may need a tool that is compatible with your chosen platform and that can export or publish your VR data visualization in a suitable format. You may also need a tool that can optimize your VR data visualization for your hardware specifications, such as resolution, frame rate, or controller input.

3 Your design goals and audience

The final thing to consider is what you want to achieve and communicate with your VR data visualization and who your intended audience is. Depending on your purpose and context, you may need a tool that can help you design your VR data visualization according to some principles and best practices, such as clarity, accuracy, interactivity, or storytelling. You may also need a tool that can help you customize your VR data visualization to suit your audience's needs, preferences, and expectations, such as accessibility, usability, or engagement.

4 Some examples of VR data visualization tools

If you’re looking for ideas and inspiration for your VR data visualization project, there are several tools you can explore and try. A-Frame, Unity, Unreal Engine, and Vizor are all examples of such tools. A-Frame and Vizor allow you to create VR data visualizations with HTML and JavaScript or a drag-and-drop interface, respectively. Unity and Unreal Engine require C# scripting or C++ programming with Blueprints visual scripting. All of these tools support WebVR and multiple VR platforms and devices, such as Oculus Quest, Google Cardboard, HTC Vive, or Windows Mixed Reality. You can export or publish your VR data visualizations as standalone executables or web applications.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?