As part of the launch of our newly established focus areas at Visual Arena, we want to arouse interest in data visualisation and encourage involvement in it. Together with our partners, we aim to highlight the challenges and the development opportunities. Here we find out how Josefine Sternvik, a strategist in the data and analysis unit at Region Västra Götaland, views the visualisation of data.
How do you use data visualisation in your everyday work?
I use visualisation to make data more accessible on different levels, which means that the figures become attractive, understandable and applicable for users. If data does not attract attention and bring insights for the people using it, it is meaningless from a strategic analysis perspective. In other words, visualisation is a powerful tool for bringing to life all the information that we have in our systems. And in an organisation as large as Region Västra Götaland we have many systems containing a huge amount of information. Using visualisation we can represent entire concepts and also trends, deviations and connections in the data. We can make more or less complex calculations and data models easier to understand and, as a result, create data-driven tools for decision-making.
What challenges do you think are involved in the visualisation of data?
There are clearly many challenges involved which include everything from the visualisation itself to the personalities of the sender and recipients. Issues such as trustworthiness, reliability and responsibility play a central role, as well as questions of prior understanding, perception and interest. This is all about using the visualisation tool in the right way for the target group and the purpose (the aim of the visualisation). One major challenge is ensuring that the recipients understand and interpret the data correctly (as it was intended) and, at the same time, can rely on the presentation and the data behind it being valid and trustworthy.
I believe there is also a general challenge on an overall level which involves identifying the potential of data visualisation and exploiting it to the full. In many ways we have taken advantage of computers’ ability to create more and more complex data models, but we are not combining them with intelligent, meaningful visualisations that make it easier for us to absorb the information or the message.
What challenges are you facing in your organisation?
In my opinion, one of the main challenges that we have to overcome in our organisation is understanding and working with the entire chain. We spend a lot of time cleaning, structuring and modelling data for analysis, but we often completely forget about the last stage, which is the visualisation. The issue is a complex one because it covers everything from time pressure to skills in visual data communication and access to the right visualisation tools. It is rare for the same person to have skills in data processing, modelling, statistical calculations and data visualisation. The challenge here is to coordinate and synch the processes but also to identify and fill the skills gap.
Then, of course, there are the challenges relating to visualisation in the context of data security and the protection of personal integrity. There is also the problem of conveying the same picture of an event or occurrence to very different target groups or to members of a target group who have widely varying perceptions of what has happened.
What do you believe is the potential of Visual Arena’s initiative in this area?
I think we have a lot to gain by creating connections and a platform for promoting and sharing experiences of visualisation issues. Data visualisation is a large, complex and wide-ranging area with a lot of different inputs and outputs. By working together and tackling an issue from different perspectives, I hope we can move this up the agenda and develop our own and other people’s skills in the area.
In an ideal scenario what impact would visualisation have?
My hope is that with the help of visualisation we will gain a better understanding and make better use of the information we have in our systems. On that basis we can then be proactive rather than reactive.