This post is part of a series on visualizing data.
Demand for data visualization on mobile devices is on the rise, both in the consumer and business spaces. Whether it is stock price performance or sensor fluctuations in a production plant, data in enterprise helps in monitoring operations, optimizing processes and quickly making informed decisions. One of the challenges in providing uninterrupted access to visualized information is the drastic reduction in screen size when moving from a desktop or laptop to a tablet or a smartphone. Best practices for print or large screen graph presentations are unsuitable: chart titles, axis labels, and other graph elements on a small screen are clutter rather than useful information. Nonetheless, effective data visualization on mobile devices can be accomplished by following these recommendations.
Before starting graph design for a mobile screen, gather particulars about what kind of data and what kind of format should be presented so that the charts best meet your users’ needs. For example, while temperature data are typically presented on line graphs, a user who really needs to know only how today’s temperature compares to tomorrow’s forecast might be completely satisfied by a numerical representation of a few data points rather than an actual chart. Understanding how users utilize information rather than in what form they expect to see the data will give designers more freedom to explore functional solutions to the problem.
Visualized data, when accessed on a mobile device, are typically part of an app that was built for a specific function. For example, various banking apps show user account balances, pending payments and even breakdowns of various spending categories. When a user engages with an app, she has a specific purpose which provides context to the data that will be accessed. For that reason, graph titles, axis labels and other supporting elements can usually be omitted.
Mobile device as a data display platform is great for interactive graphs. First, screen orientation (portrait vs. landscape) affords different pros and cons for chart displays. While portrait mode may work very well for a bar chart with a few data points, landscape mode is superior for line graphs. Second, interactions with the graph offer numerous opportunities to provide the user with detailed information that he may need while avoiding clutter on the screen. For example, pinching and zooming on a line graph could show the user changes in data over different periods of time, affording a historical glimpse of the trend as well as a very close look at data over the last hour. Similarly, tapping on individual bar graphs could bring up a modal containing a precise data label for the value.
Moreover, isolating a data point from a graph could give user access to detailed information about the data, allow her to take specific actions such as forward data to a colleague, attach a note, print graph and so on. Alternatively, a drawer that contains detailed information and slides onto the screen from the side of the graph is a good way to avoid visual clutter while increasing data density and preserving more specific information. Here, the user would only need to tap on a point in the graph to access details.
When designing the chart for a mobile app, especially when it is meant to support business processes or tasks, it is critical that information is legible for users given their work conditions. For example, if app users work on day and night shifts, the graph design should accommodate different lighting conditions for this group. Graphs with higher contrast work best in varying light conditions. Charts that contain multiple data sets (more than one line, for instance) require even greater contrast as two lines of similar hue may be indistinguishable from one another on the device screen.
Additionally, typography should follow the information hierarchy using appropriate size and weight for the level of importance. Avoid compressed type used in print materials as it will be more difficult to read. Similarly, avoid creating interactive graph elements that are smaller than suggested by guidelines for tappable areas. Moreover, assess how modals and pop-ups that are used to supplement graphs affect the users’ ability to extract meaningful information. Conducting a usability test with the graph and measuring the Standard Usability Score (SUS) will help ensure that visualized data meets users needs effectively.
User research should inform design requirements for data visualization. By stripping down graphs that are typically made for print and large screen presentations to their bare bones, you will be able to reduce chart clutter and help your users to better comprehend the presented information. Taking full advantage of the interactions available on mobile devices and weighing the pros and cons of various graphing libraries available to the developers will help ensure that the graph will be interesting, engaging, and, most importantly, informative to your users.
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