The Visual Future: from the Internet of Things to the Visualization of Things
The Visual Future
Data is not just growing. Data is also diversifying itself. New types of online datasets are overcoming classical on-premises ones. From social media analytics to data generated by smart devices, the IoT movement rapidly unfolds to be a VoT (Visualization Of Things) movement, and new measures (comments, views, likes, calories, laps, heart rates, etc.) are paving the way for new types of visualizations.
From the IoT perspective, people do not just collaborate on a dashboard after it is published, but they also have to collaborate on a dashboard while it is being created - with their own data. What we see happening in the world of the personal quantified self movement will come - sooner than expected - to the world of business. The VoT trend is already fitting big data in small maps by multiple path, phenomena intensity and frequency distribution representations.
Complex timelines are also catching up through wave representations and additional charts to the main line can add a granular level of detail to each point in time. These visualizations are best used for illustrating the long tail effect of influence over time.
Another major type of new visual model that is emerging is in 3D interactive analytics - a model that can add a lot of value to the depth view of one’s data but can also create confusion in a matrix-type of universe where - even though trends are revealed from the data - the information is too much for the human eye to take in.
3D models are becoming useful particularly for outlining relationships between far points in a data set, following long tail correlations and ranking outlier values because they offer a network view, the user being able to rapidly identify essential nodes and highly dense webs.
Last but not least, as algorithms, equations and functions are becoming more and more invisible in user interfaces due to the evolution of both traditional query languages and of the natural programming language, fractals - as detailed patterns repeating themselves - are becoming a viable option for data visualization in the near future. Even though they are mathematical forms, fractals have been widely used in the world of digital art so the idea to use them in visual dashboards may trigger the accomplishment of the aesthetic information goal.
Due to the developments in data visualization set out in this article (and others), we believe that we are no longer talking about individual observers of data. There are multiple observers who can change roles in order to obtain a 360° view of the data they analyze. There are multiple layers of depth and time length through which these observers can understand potential algorithms of previously unexpected events.
Therefore, along with becoming an essential tool for revealing opportunities, the visual dashboard may well be the world’s next best risk avoidance tool, too.
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