What are the most effective 3D graphics for data visualization?

1 Why use 3D graphics?

3D graphics can be used to enhance data visualization, depending on the purpose and audience of your project. For instance, 3D graphics can more realistically and intuitively show spatial relationships and depth, particularly for data that has a physical or geographical dimension, such as buildings, landscapes, or human anatomy. Additionally, 3D graphics can create immersive and engaging experiences that attract attention and curiosity, particularly for data that has a narrative or emotional dimension, such as stories, scenarios, or simulations. Furthermore, 3D graphics enable more interactivity and exploration, allowing users to manipulate, rotate, zoom, and navigate the data from different angles and perspectives - especially for data that has a complex or dynamic dimension, such as networks, systems, or processes.

3 How to design 3D graphics?

When designing 3D graphics, there are several aspects to consider, such as scale, color, and lighting. Scale affects the relative size and proportion of the elements in the 3D graphic, and a consistent and appropriate scale should be used to match the data and the message. Color affects how the data is distinguished and emphasized, so you should use a harmonious and meaningful color scheme that reflects the data and the theme. Lighting affects how the data is shaded and highlighted, so you should use a realistic and consistent lighting that enhances the data and the depth. All of these design considerations are important for creating a 3D graphic that accurately conveys the message.

4 How to evaluate 3D graphics?

When evaluating 3D graphics for data visualization, it is important to assess their effectiveness and efficiency, in addition to their aesthetics and novelty. Clarity is the degree to which the 3D graphic conveys the data and message accurately and precisely, while simplicity is the degree to which unnecessary or redundant elements are eliminated. Functionality is the degree to which interactivity and exploration enhance the data and message without compromising or confusing them. You should assess whether the 3D graphic uses the appropriate type, scale, color, and lighting; provides labels, legends, and annotations; uses the minimum number of models, scenes, and animations; allows users to manipulate, rotate, zoom, and navigate; and provides feedback, guidance, and navigation tools.

5 How to learn 3D graphics?

Learning 3D graphics requires more skills and tools than 2D graphics, as they involve more dimensions and variables. To become proficient in 3D graphics for data visualization, you can refer to books such as Visualizing Data by William S. Cleveland, Data Visualization: Principles and Practice by Alexandru C. Telea, and Data Visualization with Python and JavaScript by Kyran Dale. You can also take courses like Data Visualization and D3.js by Udacity, Data Visualization with Python by IBM, and Data Visualization with R by Coursera. Additionally, you can use tools like Blender, a free and open source 3D creation suite; Three.js, a JavaScript library for creating 3D graphics in the web browser; and Plotly, a Python library for creating interactive 3D charts and graphs.

6 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?