How can Data Visualisation Facilitate Decisions?
I want to show an interesting way we can use technological solutions using our project called Smart City Lübeck. Namely, we have developed an application for data visualisation, which offers officials and citizens of Lübeck the possibility of easy display and use of data. What this brings in practice, I will explain below.
How can we use the data?
In the digital age, data and various information are something that many devices and systems collect at practically every step, every second of the day. Let’s take the city as an example. A huge amount of data is collected with various devices, systems and databases, for instance, about residents, sensors, traffic, weather, kindergartens, schools, etc. This information is intended for the public good and, in the case of proper processing, allows a holistic view of the various segments of interest to the officials or citizens. If I list only a few ways of practical use, it is possible to find out, for example, which part of the city is the safest, the sunniest, how much rain falls in which months, which parking lots are currently free, etc.
A key challenge: the dispersion of information
Therefore, all this information exists, but it is incredibly fragmented in many systems and unconnected to each other, making it impossible to gain broader insight. Based on the European Union initiative, we took on the challenge of connecting this data and combining it into a common form. It is crucial that data aggregation needs to be approached in such a way that we can compare it with each other in the next step, as only at this point do concrete solutions begin to emerge. However, it is necessary to be aware that this is a vast amount of data generated all the time, which is a great challenge.
Smart city visualisation
As part of the project, easy.bi developed a web application as an example of how data could be visualised, the information provided in an accessible way and presented as transparently as possible.
There were two key challenges.
1. To find a solution on how to combine all available data to extract meaningful information from it.
2. To find ways to present this information so the user recognises the added value.
An example of how data comes to life in practice
We have solved both of the above challenges with several approaches and offered insight into the broader picture, which has a high added value for data users. One such example was that we combined data on traffic accidents and kindergartens and came up with a holistic picture in one step that most accidents happen near two kindergartens. This is an essential piece of information for those responsible for taking action on logistics and road safety. They were able to make a more informed decision and first focus on these areas by setting up warning signs and other traffic regime adjustments.
Another example was the interpretation of various available data on voters. With proper aggregation and integration, we could see that there is no such interest in elections in a particular part of the city, so those responsible in these parts of the city could raise awareness by placing posters, encouraging active participation in elections and the like.
Smart City visualisation is also primarily intended for residents, who can use data visualisation to obtain a lot of information that interests them. For example, when deciding to move, buy a property, choose a school, find parking spaces, etc. or when they want to get many other daily up-to-date information instantly.
This type of visualisation aims to present the data in a transparent, attractive and, ultimately, interactive way, enabling more in-depth insight and more straightforward, faster and more optimal decision-making.
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