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.
John Schwartz, Data visualisation competition for think tanks
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… numbers that didn’t 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: “No. Never get rid of the charts and graphs. Everyone wants to see them.”
It must be telling that, more than a year later, I still remember this exchange. Do they? Does everyone want to see all the numbers? Is it absolutely necessary to back up every statement with numbers that sometimes don’t make sense? Are we so afraid of half-truths that we need hard evidence, always? What is the context around this data anyway?
I’ve 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.
If you have a ton of data and are not sure how to best put it to use, take a look at what’s 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’s on data visualisation.
As for picking the right data to inform your narrative, when creating their “Our Money!” visualisation, the Budapest Institute had to make important concessions to create a successful piece. As Ana Orosz said:
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.
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:
- What do you want to communicate?
- Who do you want to communicate to?
- What is your purpose?
- How do you want to communicate this to them?
- What can you actually do?
Oriol Farrés, project manager at CIBOD, Barcelona Centre for International Affairs, writes about opening new spaces for communication and research. As communication spaces change, think tanks, and academia in general, have to embrace new platforms to communicate their research. These offer the opportunity to reach new audiences, engage with them, and increase the chances of, ultimately, influencing policy. He describes the changing role of think tanks as:
A think tank’s role as information gatekeeper is being progressively replaced by the role of information provider, that simplifies the complex informational environment by “subtracting the obvious and adding the meaningful”.
We have written about the need for communicators and researchers to converge and find middle ground before. Oriol calls it a “coalition of brains” which will allow for top research to be disseminated in the most effective manner. (Oriol uses other great terms throughout his article, such as “infoxicated.”)
As for data visualisation, he writes:
By definition, data visualisation is a discipline that can affect positively both areas: on one hand, fuelling the capacity of the research and data analysis by improving the ability to extract conclusions and project scenarios; on the other, making the approach to results more attractive, visual and intuitive.
Back in 2013, On Think Tanks held a data visualisation competition. Making the most out of the opportunity, Jeff Knezovich gathered some advice from the judges of the competition, also offering his own:
A data visualisation should be instantly understandable; they can contain more information on closer inspection, but if it doesn’t have an immediate impact and increase my understanding of a topic, I won’t give it a second glance. In that sense, I think aesthetics are incredibly important, and that is almost always a case of less is more!”
Leonora Merry’s advice for someone trying to make sense of a lot of data:
Decide on your audience, and ask yourself – if they could understand one thing about this data, what would it be?”
As for good data visualisation, John Schwartz’ from Soapbox studio, says:
[Data visualisation] is about arranging information so your audience can clearly see the patterns and trends. In a good visualisation the data stops being just numbers and starts telling stories, explaining facts and advancing arguments.”
As for what not do, Andrej Nosko’s says:
In the context of policy research the thing that can really drive me crazy when it comes to data visualisation is, if after I look at it, I want to ask ‘so what?’”
As for Enrique Mendizabal, he wants to see visualisations as part of a bigger effort:
Sometimes they appear to be stand alone efforts. The best visualisations always encourage you to search for more information on a subject. They have to be connected to a wider communications effort.
Luckily for all our readers, we are huge on sharing resources. The internet is full of great (often free!) stuff for you to use to communicate your research. As part of the On Think Tanks Data Visualisation Competition, the team produced a series of step by step “how to’s” to support think tanks to develop their visualisations.
- For data collection, check out How to import live data with GoogleDrive Spreadsheets, for a walk through on how to import live data from the web.
- Check out How to map data using Google Fusion Tables for guidance on what do with the data you have captured.
- In How to summarise data with Pivot Tables in Excel, you will learn how to summarise that data to answer specific questions using the PivotTable utility in Excel.
- How to animate a map to see changes over time using CartoDB offers guidance on how to create maps that change over time.
- How to… merge and tidy datasets with Microsoft Excel walks you through the VLOOKUP function to merge data in Excel, used to combine two different dataset when a simple copy and paste just won’t do.
- Finally, in How to create interactive dashboards with Tableau Public, the focus shifts from maps to types of charts that might be useful when it comes to visualising data. A programme like Tableau Public can pull various visualisations together into a single interactive dashboard.
As Jeff says in Data visualisation: A pen and cantaloupe may be enough:
Don’t re-invent the wheel: As this blog and the datavis competition mini website have shown, there are SO MANY free-to-use resources out there to help make visualisations.
In an interview with Eric Barrett, from JumpStart Georgia, Jeff and Eric talk about Jumpstart Georgia’s work with data visualisations, and why they decided to embark on these projects. In short, Eric says:
We started with infographics because we wanted to challenge the status quo in Georgia. Too many organizations are lazy and don’t take their target audience into account. They just throw out content and say: “here, read this”. We see a growing trend worldwide that audiences want more and as content producers we should oblige.”
As On Think Tanks’ communications director, Jeff has written quite a bit on data visualisation and its importance in the think tank community. Jeff shares some of his experiences, as an attendee or speaker at data visualisation conferences, as a judge for On Think Tanks’ data visualisation competition, and generally as someone who has quite a bit of experience in the field. In Visualising data: both a science and an art, Jeff shares his experience when framing discussions around the topic:
As part of the data visualisation trainings that I do, I usually frame discussions around four different skills groups: research, technology, communication and design.
In an interview with Robert Muggah, author of Mapping Arms Data, Robert shares Igarapé Institute’s experience with a successful data visualisation intervention:
By presenting a large dataset in visually arresting and user-friendly manner, it has inspired “mainstream” debate, but also people associated with technology and design industries, police and justice, relief and development, and beyond (…) Researchers and practitioners will need to engage and adopt many of these visualisation and analysis tools if they are going to improve their work and trigger policy change.
So, why data? John Schwartz says it best:
Good data empowers individuals, communities and campaigns. It adds force to ideas and the weight of evidence to policy proposals. When we make data more intelligible, compelling and transparent through visualisation we multiply its power to create change.
(By the way, make sure to watch the video John shares- It’s fascinating, and Rosling’s excitement whilst presenting the data makes it that more awesome.)
Don’t forget to join On Think Tanks School short course on Data visualisation: taking communication to the next level. Starting September 27.