Several software programs are available to help you create dynamic (moving) and interactive graphs for web-based publications – that is, graphs that allow the reader to change, move through and select features of the data display. Common interactions include allowing the reader to filter subsets of data in and out of the graph, and ‘hovering’ over data points to reveal their precise values.
Designing interactive data visualisations
Interactive data visualisations can be a very powerful way for readers to personalise and strengthen their understanding of your dataset. For example, viewers of a website that shows graphs for cancer statistics during the past decade may want to select data for their demographic group only. This enables the reader to make intellectual connections and observations that might otherwise be hidden or difficult to comprehend.
In addition to the design of your website, the level of data interactivity within graphs will depend on the type of data you have and whether the dataset is large enough to show adequate detail across demographic or other categories. It is also important to consider whether possible interactive filters and comparisons are appropriate and meaningful. For example, if there is no scientific or theoretical reason to expect differences between men and women on a particular measure of health, it is not appropriate to enable readers to filter the graphed data by sex.
In designing interactive data visualisations, it is important to consider:
- the guiding principles of clarity and accuracy in data presentation
- choice of visual format (see Choosing the right graph for your data)
- good visual design (see Functional design for graphs)
- technical functionality
- a clear reason for people to interact with the data
- visual appeal and the ‘fun factor’.
It is important to avoid having gimmicky animation or irrelevant functionality that obstructs the data message or the reader’s engagement with the data.
Data visualisations can be constructed in numerous ways, including:
- a simple, predetermined sequence of static graphs that either plays automatically (like a video) or requires users to click through from one to the next
- a continuous (but not interactive) animation of the data (eg time-series data that evolve over the duration of the animation)
- an interactive data visualisation using software such as Tableau, where users can click on, or hover over, different elements of the data visualisation to explore the data (eg ‘pop-up’ details for individual data points, or selecting categories of data in or out of the display)
- dynamic 3D data visualisation connected to a content management system, database or spreadsheet using software such as Tableau, D3.js, Exhibit or Visual.ly, which enables the user to interact with and explore the data (eg by zooming in on a selected data series, or clicking on a data point to see its other connections ‘explode’ into detail)
- game-style data visualisations, which help readers understand a message by leading them through the data, often giving them a score or performance rating at the finish.