Data visualization is an effective approach for displaying different types of data, both big and small. Converting information into visual text makes it easier for the human brain to perceive data and make inferences. The main purpose of data visualization is to help identify patterns, trends and anomalies in large data sets. Visualization is a key element in almost all professions. It is an element of data processing that specifies that collected, processed and modelled data can be visualized for inference.
Animations can be used to bring data to life in both the visual exploration and narrative phases. The visualization of animated data can engage the viewer in different ways. The visualization of static data, especially individual data, can be persuasive and aid decision making. Animation enhances these benefits.
Animation can benefit data visualisation in a number of ways.
The renowned Hans Rosling has explored different ways to make storytelling more engaging. Handling explored different ways of storytelling and was able to create a range of dynamic data visualizations related to financial and physical well-being. He showed how to harness the power of visualization to create emotional impact and clear communication. He also explained the link between animation and data visualization. Data visualization animations are an interesting topic and a very powerful tool to engage audiences on a deeper level through emotions. Users can use different presentation styles to tell stories from data. The main purpose of data animation is to improve communication and promote change.
It helps to intercept change:
The visual analysis helps to communicate clearly, but also to explore and analyze. Without animation, it is difficult to capture the movement of data points from one place to another as the graph changes or is filtered. In such cases, it is appropriate to use an animation based on a concept called object persistence. This allows the transition of a graphical element to be tracked. Object persistence allows individuals to understand and see the changes, rather than having to identify each new point. Simple changes in graphs and trends affect our understanding of the data. We relate to the insights we gain from the data.
The main purpose of data visualization is to let the viewer know how something is changing in different situations. Animation can be useful for time series or logically ordered sequences. These can slow down the communication process, but can benefit from a new level of engagement, especially with target audiences who do not normally engage with data.
Studies have shown that animation has improved the quality of data at both syntactic and semantic levels of analysis. Animation has shown significantly lower error rates even for highly predictable transitions. The results also showed a preference for animation as participants found it more usable and engaging. In addition, stage animation proved to be more useful than live animation in most cases.
Nowadays, many business managers are increasingly interested in visual analysis. Animation plays an important role in the quality of insights derived from data. It works on a psychological level, connecting viewers with the data and engaging the creative and narrative side of users.