Making the Invisible Visible
The Knowledge Share is a series of events for thought leaders and domain experts, to present and discuss interesting and thought provoking topics here at Tobias & Tobias.
After a recent successful collaboration with Signal | Noise on a data visualisation project, we were impressed with their approach and depth of thinking, so invited them to share their thoughts on the current state and trends around data visualisation and big data.
The realisation that so much data is constantly being collected about us has become a permanent headline in the international press in recent years. Over the last decade, corporates have been storing huge volumes of personal and behavioural data about us, through freely available services that give us a perceived value.
For many, these services have become tightly integrated into our digital habits, creating an ever increasing willingness to submit greater depth of personal information. Dependence has grown so great that the thought of opting out of services such as Google or Facebook seem completely alien.
This data has become extremely valuable and now provides a distinct competitive advantage to commercial organisations. Historically, companies were valued based on their assets, but when Facebook became a public company, it was valued at over $100 billion, although its assets were only valued at approximately $15 billion. This difference came from the recognition of the potential value of its user data.
One key element in any conversation about data is making sense of it, and the term data visualisation is often mentioned. So what is data visualisation all about?
1. Data visualisation helps us make sense of the world
Data is a layer on top of the real world. Data visualisation reveals the things we can’t see. By combining static information design and interaction design, it is possible to explore and manipulate data.
2. Data is entertaining
Charts and graphs previously accompanied journalism, but now data is often the content; it is seen as ‘datatainment’. With infographics it is possible to present a lot of information on one page, to give people a good overview in a short time.
With data visualisation, it is important to strike a balance between simplicity and complexity, by distilling what is important and telling an engaging story through the use of graphics, colours and images.
The mixture of statistics and sport goes back to bookmakers and TV shows like Family Fortunes, but these days it is more interactive with things like the Heineken Star Player app.
Signal | Noise was interested in the world of sports data visualisation so created the Transfer Window visualisation. This shows where football players have been transferred and how much for, via a simple and interactive interface. After a great response, they’ve launched a second version to show ‘bang for buck’.
3. Information is beautiful, but prediction is magic
Data visualisation can be beautiful, for example, LinkedIn’s connections maps and Foursquare’s check-in maps.
When there is enough data, predictions can be made. The target can predict when customers are pregnant and Visa can learn about lifestyle habits and reliability. However, this kind of insight can make some people feel uneasy!
4. The closer you are to the data, the more powerful you are
With data visualisation, it is often about demonstrating ownership, by presenting an understanding or manipulation of the data.
Maps are an early example and closely associated with power. Matthew Maury gathered data from thousands of ships logs to compile an atlas of seas, helping ships get somewhere faster or safer; ultimately giving an advantage.
5. Data has more opportunities
Data could be pooled from multiple sources to see relationships or find out things you don’t know about yourself, such as the link between your sleep pattern and bank balance.
There could also be great benefits to society, for example combining health and lifestyle data to help prevent illness.
Companies hoarding rather than sharing data could be a missing a trick, as there could be more to gain if data was treated like open source software.
6. With great power comes great responsibility
Once your data is out there you don’t really have control of it or know how it will be used in the future.
It can be a problem if data is tied to an individual rather than aggregated. Knowing between five and ten locations can be enough to pinpoint an individual and this could be exploited.
This highlights the need for regulations or a code of conduct for the collection and use of data.
There could also be more equitable models where people get nano payments from the profits made from their data.
Many thanks to Signal | Noise for presenting and debating this topic with us. Please contact us at email@example.com if you’re interested in getting involved in a future Knowledge Share event.