A new way to approach data
We live in the era of big data, information overload and 24/7 internet access, but people feel more disconnected than ever. The realities and problems we face today are so big and complex that it is complicated to understand them without numbers. At the same time, reducing these problems to numbers makes societies numb to them.In order to make sense of this world and to trigger any kind of action, we need to use statistics, but also art, science, technology and many other disciplines to give context, include emotion and finally create empathy and connections. As the wise Hans Rosling once said: “The world cannot be understood without numbers, but it will not be understood with numbers alone”.
Refreshing data
When we think of data science, we often imagine long spreadsheets, machine learning models and programming tools from which we can directly extract knowledge. But in order to understand the inherent complexity of today, we need alternative visualisation strategies that use many other tools, such as design, animation, social sciences, illustration. In fact, data scientists, designers, students and artists of all kinds are already working in this direction. Here is a small selection of some of them:
How can we measure culture?
The aim of the Me-Mind project was to create tools to quantify the effect of culture within cities and communities. In this journey toward building the tools for culture quantification, we asked exhibition visitors to reflect, what effect culture can have on them.
Cultural experience as statistics
While some people keep track of their activities and some don’t, there are also different institutions that keep track of what we do. Our activities are transformed into statistics, our individual experiences are generalised to collective experiences, and based on both decisions are made. To illustrate how individual experience becomes collective we invited visitors to contribute to this creation with examples from their own cultural consumption.
Photos: ENM, Domestic Data Streamers