This blog is part of a three part series ‘Diving deep into open data’. Other blogs in the series are:
A Successful Camp: Open Data, Governance, Digital India and Caddisfly
Notes from the Open Data Development Fair 2015, the Netherlands
DataPorn850
Above: The quantity of data being collected is growing rapidly. This picture show the world travel movement and communications recorded on Twitter. Photo by Eric Fsicher.
Having been involved in the organisation of the Open Development Camp in 2012, 2013 and 2014, this year was the first time I attended the event as just a visitor (and presenter in one session). 

For the 2015 edition, the organisers, Open for Change joined forces with the Partos Innovation Festival leading to a combined event called the Connected Development Festival. It was great – the atmosphere and people were very inspiring.

There was one session in particular that caught my attention and inspired this blog;  ‘Development data, one step beyond’ – a session moderated by Pelle Aardema of Open for Change with presentations from Leonardo Pérez-Aranda (Oxfam Intermón), Theo van de Sande (Ministry of Foreign Affairs NL) and Rolf Kleef (Open for Change). 

What struck me most in this session was Rolf’s view on the future of development data. He used the term “data porn”. I had never heard this phrase before, but it’s so incredibly accurate. He defined it as: “attempts to make sexy visualisations with naked charts and maps. Or even those dreadful things called infographics…” Data porn may be visually attractive for a short while, but if you look closer there is not much substance to it and it doesn’t really tell us anything. Rolf’s full talk can be found in this (must read!) blog.

The term data porn intrigued me and I started to look critically at data visualisations on the web. I noticed that a lot of them did not really tell a story, but were just made to impress their audience, and thus could be classified as data porn.

Personally I see this as a growing problem of our time, as currently the quantity of data that is being collected is increasing at a rapid pace, but analysis and visualisation skills are lagging far behind. It’s moving so rapidly that 90% of the data in the world today has been created in the last two years alone.

Working for Akvo I’ve witnessed this problem too; people use Akvo FLOW to collect data, but quite often lack the skills to do the sometimes complex analysis and visualisations they would like to with it.

To explore the problem of data porn a little further I want to dive a bit deeper into data visualisations, starting with the the question – why do we make them?

Why do we make data visualisations?
Data visualisations make data understandable. Many people are what I  like to call ‘data illiterate’; if you send them an excel file with data containing all the answers to their questions, they look at you confused or give it to somebody in their organsiation who does have the skills to analyse the data and make visualisations from it.

A lot of people want an easy to understand visualisation that shows them what they want to know – they’re not interested in the underlying data. It’s a bit like a cake – people don’t want the ingredients, they want the result. But just like a cake, the result depends on the quality of your ingredients and how you use them. There is always a subjective aspect to ‘transforming’ data into a visualisation.

So how do data visualisations become data porn?
Data can be used for different goals, such as communication, informing, reporting, marketing and management. There is also a big difference between internal and external use and between interactive and static visualisations. (If you are interested in reading more about visualisations, I recommend this article.)

Data being used to communicate externally is at biggest risk of being turned into data porn in my view. An organisation may want to publish a sexy graph, table or chart showing how well they’re doing (and how digitally literate they are). There is a strong temptation to focus on the data that shows the best results, visualising this beautifully and manipulating it so that it communicates a particular message the organisation wants to send. The example below comes from this blog, which highlights three of the most common misleading ways of visualising data. This one shows the effect of changing your y-axis.
Below: same data, different y-axis. From How to lie with data visualization, by Ravi Parikh
 Y axis 650
So we don’t want data porn. But we also don’t want our data to be like an advanced quantum physics class given to social sciences students – complex and difficult to understand if you don’t have the correct knowledge.   I think we should try to create attractive data narratives that people can understand, that communicate key facts and prompt you to form your own opinion about the data and the visualisation.

A great example of someone who tells stories in an attractive way using data is Hans Rosling. I would definitely recommend his website gapminder.

Creating attractive narratives instead of data porn is easier said than done, but I think taking the following steps could help: 
  1.   Improve data literacy to help people understand data better, realise the choices made when visualisations are created and spot data manipulations.
  1.  Improve data visualisation and analysis skills globally so that we produce better quality narratives that communicate more clearly and accurately.
  1.  Further develop the profession of data journalism – so that created data visualisations are analysed and viewed critically by trained professionals who can also share the data stories.
  1.  Open up the data underlying published visualisations to make it accessible to the public so they can use the data to create their own visualisations. An important note with this is that it has to be done in a responsible way, taking into account data privacy, and providing good metadata.  
It’s important we get this right because what is at stake is people’s trust in data, and the intrinsic value of data itself.  For this reason I would like to ask everybody reading this blog to start (or keep) looking critically at data visualisations. And if you have any ideas about how to move away from data porn or additional blogs or initiatives that we all should know about, please share them below in a comment, or tweet them to me @JosjeSpierings.

Josje Spierings is project manager at Akvo, based in Amsterdam.