How do you create AR data visualizations for user scenarios?

1 Identify the user scenario

The first step is to identify the user scenario that you want to address with your AR data visualization. A user scenario is a description of how a user would interact with your AR application, what goals they have, what challenges they face, and what information they need. You should consider the user's profile, context, tasks, and preferences, and define the key questions that your AR data visualization should answer. For example, a user scenario could be: "A firefighter wants to see the temperature and smoke levels of a building on fire, and the location of other firefighters and exits, using a smart helmet with AR glasses."

2 Choose the data sources

The next step is to choose the data sources that you will use for your AR data visualization. Data sources are the databases, APIs, sensors, or other systems that provide the data that you want to display. You should select the data sources that are relevant, reliable, and accessible for your user scenario, and that can provide the data in real-time or near-real-time if needed. You should also consider the format, size, and frequency of the data, and how you will process, filter, and transform it for your AR data visualization. For example, for the firefighter user scenario, you could use data sources such as thermal cameras, smoke detectors, GPS trackers, and building maps.

3 Design the data representation

The third step is to design the data representation that you will use for your AR data visualization. Data representation is the way that you encode and display the data in AR environments, using different visual elements such as shapes, colors, sizes, positions, orientations, textures, and motions. You should choose the data representation that is appropriate, effective, and intuitive for your user scenario, and that can convey the data attributes, relationships, and patterns clearly and accurately. You should also follow the principles of good data visualization design, such as simplicity, consistency, contrast, alignment, and balance. For example, for the firefighter user scenario, you could use 3D models of the building and the firefighters, color-coded heat maps and smoke clouds, and directional arrows and icons.

4 Implement the data visualization

The fourth step is to implement the data visualization that you have designed for your user scenario. Implementation is the process of creating and rendering the data visualization in AR environments, using different tools and platforms such as AR frameworks, libraries, engines, and devices. You should choose the tools and platforms that are compatible, scalable, and performant for your user scenario, and that can support the features and functions that you need for your AR data visualization. You should also follow the best practices of AR development, such as testing, debugging, and optimizing your code, and ensuring the usability, accessibility, and security of your AR application. For example, for the firefighter user scenario, you could use Unity as the AR engine, ARKit as the AR framework, and iPhone as the AR device.

5 Evaluate the data visualization

The fifth step is to evaluate the data visualization that you have implemented for your user scenario. Evaluation is the process of assessing the quality and effectiveness of your AR data visualization, using different methods and criteria such as user feedback, usability testing, data analysis, and visualization metrics. You should evaluate your AR data visualization from different perspectives, such as user satisfaction, user engagement, user performance, data accuracy, data clarity, data relevance, and data insight. You should also identify the strengths and weaknesses of your AR data visualization, and the opportunities and challenges for improvement. For example, for the firefighter user scenario, you could use surveys, interviews, observations, and eye-tracking to evaluate your AR data visualization.

6 Iterate the data visualization

The sixth and final step is to iterate the data visualization that you have evaluated for your user scenario. Iteration is the process of refining and enhancing your AR data visualization, based on the feedback and results that you have obtained from the evaluation. You should iterate your AR data visualization in an agile and iterative manner, making small and frequent changes to your data sources, data representation, data implementation, and data evaluation, and testing and validating them with your users and stakeholders. You should also document and communicate your iterations, and measure and report your progress and impact. For example, for the firefighter user scenario, you could use a version control system, a project management tool, and a dashboard to iterate your AR data visualization.

7 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?