Seminar: CBS Datavisualization – Bas Broekhuizen
With this seminar statistic data supplier CBS invited several data visualization professionals, to present their work in order to explore the data visualization field and the different disciplines involved. The main question that rises today is how to uses the benefits of presenting complex data, in an informative way for the bigger public.
Visualizing data in an interactive way is seen as the next best thing, as it combines several disciplines from data mining, programming and interactive graphic design amongst others. As interactive info graphics generate more attention, data sets grow bigger as we speak, demanding for less abstract visualizations. Herewith statistical data becomes important in a new way, as it functions as input for presenting complex data in a graphic interactive manner to the public. With this new frontier in sight, the questions that are posed at this seminar are of an exploration, yet important quality. For starters, how to make a data visualization, which tools to use that provide the best graphical view, how can data visualization be used in structuring large and complex data sets, and how to make sure the interactive aspect of the data visualization really contributes to a better understanding of the data?
Hopefully the report of this day will contribute to the explorations and insights of the CBS and the data visualization field. Since the inspiring presentations of the day, cannot be discussed at once of limited space, I decided to start posting with the first presentation of the day, right here, and work my way through the day in a small series of further posts.
Professor of Journalism of the UvA Media & Culture Institute Bas Broekhuizen kicked off whit his presentation. He gave an introduction of the data visualization field, stating that data visualization is a way to communicate the story behind the data. For data visualization has the function to interpret, get insight of, analyze, captured and personalize data.
Interactive data visualization benefits from an upcoming popularity, as info graphics pop up in all layers of society. In commercials, public service tools, infotainment , higher culture and in collecting all kinds of data about ourselves with the latest apps. Herewith the idea arises that data visualization is a form of popular culture, a way to express developments in society. The digital age revolves in a visual world, for graphical data is everywhere around us, providing an insight into the complexity of our time. Info graphics are recognized as imagery language to instruct and explain, often not so much used as data visualization. These kind of graphics, often do not provide an insight in the used data of figures and content itself. They are made to take notion of a set message, to inform or entertain. So are (info) graphics a hype, answering to our need to entertain and occupy ourselves? And is data visualization the next step in this development? I think there is more to it, as Broekhuizen explains.
The first part in his introduction to the field, is to note the difference between an info graphic and a data visualization. For an info graphic is not a data visualization per se, the difference can be noted in showing the data within the visualization, according to Broekhuizen. To understand the difference a lineage of data visualization is provided, containing of two starting points. The first point starting with graphic communication in cave man drawings and the starting of writing. The second within the development of science with the known examples of William Playfair and John Snow showing important insights, that are drawn from the visual displays of complex information. Towards the scientific field of information visualization, know from of the 1970’s where scientist used visual displays for further research purposes. New genres of data visualization occurred with the benefits of this earlier research. Where data experts scientists combined interdisciplinary research to explore new ways to visualize data. Their insight brought a lot of new ways of visualize large data sets, such as now a days on the Internet. For example in the Open Data movement. And large corporate businesses that provide data sets, to state their transparency of cash flows and gained goods. And with the mentioned Open Data movement, also governments provide their data online. Such as in the US, Uk and the Netherlands.
As seen the field of data visualization is not new, though the current circumstances result in new possibilities. One of the new features of data visualization nowadays is that of interactivity and the availability of interactive graphic tools, such as Tableau, Google and Many Eyes.
The possibility of interaction is one of the most important distinctive for data visualization. For Broekhuizen interactivity is; the extent to which form and content of a message can be influenced in real time. Speaking of form and content the aesthetic question comes in mind, should data visualization be beautiful or effective or both?
Which brings us to the Tufte and Holmes discussion of ‘tell the story vs reveal the data’. For Broekhuizen a data visualization should be engaging, it needs to pull its public towards the visualization to get them interested in the message. Applying this on interactivity, he explains, that on the one hand, interactivity enlarges the public’s involvement, as well as it enlarges the public’s cognitive abilities. Which can result in a downgrade of understanding the message. This paradox of interactivity can be overcome by rethinking the goal of the data visualization, he says. Herewith his ideal structure of a data visualization is a visualization with an first overview and zoom layers and filters, for further exploration options. Though this ideal structure is not leading, he says. A good alternative for this can be the possibility of narrative.
Herewith the first step towards the land of data visualization, is to ask oneself which function the message has that is to be visualized. For Broekhuizen, this can be to inform, persuade, entertain or share, each with their own strategy, that can be given their own function within the data visualization.
My first impression after this presentation, is that it seems that all the ingredients of data visualization are present, though the right recipe is not provided yet. However it may taste like in the near future, I am sure it will be beautiful.