{"id":3445,"date":"2016-09-13T21:30:32","date_gmt":"2016-09-14T02:30:32","guid":{"rendered":"https:\/\/onthinktanks.org\/articles\/\/"},"modified":"2016-09-13T21:37:20","modified_gmt":"2016-09-14T02:37:20","slug":"data-visualisation-how-numbers-tell-a-story","status":"publish","type":"post","link":"https:\/\/onthinktanks.org\/articles\/data-visualisation-how-numbers-tell-a-story\/","title":{"rendered":"Data visualisation: how numbers tell a story"},"content":{"rendered":"

Data is not boring. Data can explain social and economic trends and start new conversations. Data can inspire new ideas, and it can test how they work. Data can challenge those in power. Data can change the world.<\/span>
\n<\/span><\/p><\/blockquote>\n

John Schwartz, <\/span>Data visualisation competition for think tanks<\/span><\/a><\/p>\n

 <\/p>\n

About a year ago, I was designing a report on a public health intervention. Although I am sure the content was fascinating to some, for the average reader, it was far from riveting. There were numbers everywhere\u2026 numbers that didn\u2019t say a whole lot but seemed impressive (basically, big numbers). It was data overload, where every single number recorded throughout the one year intervention had been charted and graphed. Talking to a friend (who happened to be a WHO representative) about said report I casually mentioned that I was contemplating dropping some of the charts and graphs. His advice: \u201cNo. Never get rid of the charts and graphs. Everyone wants to see them.\u201d <\/span><\/p>\n

It must be telling that, more than a year later, I still remember this exchange. Do they? Does <\/span>everyone<\/span><\/i> want to see <\/span>all<\/span><\/i> the numbers? Is it absolutely necessary to back up every statement with numbers that sometimes don\u2019t make sense? Are we so afraid of half-truths that we need hard evidence, <\/span>always<\/span><\/i>? What is the context around this data anyway?<\/span><\/p>\n

I\u2019ve learned that not all data is relevant after all. You have to be discerning with your information, make sure it feeds a narrative that speaks to your target audience, and present it in a way that people can actually understand it enough to have an impact on them. Research, of course, is driven by data; data that gives insight into the state of the world today, and can objectively inform the public about our realities.<\/p>\n

If you have a ton of data and are not sure how to best put it to use, take a look at what\u2019s out there. Look at what your peers are doing with their data, and find the best way to use your own to inform your audience and generate the impact you are seeking. Data visualisations, of course, are a great tool for this. This series is complete with opinions, advice, and how-to\u2019s on data visualisation.<\/p>\n

As for picking the right data to inform your narrative, when creating their <\/span>\u201cOur Money!\u201d visualisation<\/span><\/a>, the Budapest Institute had to make important concessions to create a successful piece. As Ana Orosz said: <\/span><\/p>\n

We at the Budapest Institute are economists. Therefore, when we think about the budget, our heads are chalk full of numbers about nominal and proportional sums, longitudinal comparisons, time changes, international comparisons, and so on. It required a lot of heated exchanges with the designer as well as self-restraint to realize that in this genre [data visualisation], less is more.<\/span><\/p><\/blockquote>\n

At On Think Tanks, we have quite a bit of content on communications for research. Data visualisations are part of communications activities and, as such, should follow the same basic process:<\/p>\n