4/2/2018

Datawrapper River

 

A new resource to share and reuse charts.

Earlier this week, Datawrapper launched an extension, called River, to streamline the exchange of charts and maps between data sources and newsrooms. 

While there is no shortage of great data sources, many of which offer data for free via dedicated websites and portals, time poor journalists are limited in their capacity to truly harness these stores. To close this gap, Datawrapper River allows data sources to upload visuals, which can then be easily customised and resused by newsrooms around the world. 
 
Image: Lisa Charlotte Rost.
 
In effect, the tool works like a newswire for visuals - sources are able to increase the reach of their data, while journalists are able to quickly identify cool stories or add data to breaking stories.
 
We spoke to Mirko Lorenz, Datawrapper's Co-CEO and Founder, to find out more.
 
DDJ: What inspired Datawrapper River?
 
ML: Our goal is to shorten the time needed to publish data on a news page. That is what Datawrapper is all about. The River an extension. Why should a journalist have to download data from the statistics office when he could get the chart? It's kind of an obvious idea, a next step. But it had to be built to make the point.
 
To get there we asked ourselves: What steps of the workflow do we not cover? What else can we do? So far we have contributed to the visualization part, but not to the search/clean/check data part. If you have ever created a visualization, you'd know that substantial work has to be done by the journalists finding, downloading, filtering, etc before getting to a publishable chart.
 
 
Image: Lisa Charlotte Rost.
 
To go even further backwards in time. The very initial idea which lead to Datawrapper River started in 2010, when we organized the "first" data journalism roundtable in Amsterdam with the help of the European Journalism Center. There was a great rooster of speakers that day, from the NYT, Guardian, The Times, Financial Times, etc. Simon Rogers, Lilliana Bounegru, Lorenz Matzat, Nicolas Kayser-Bril, all in one room talking about data, all very active in the DDJ community to this day.
 
There was one observation, a pattern: All those active data journalists had very special know-how. And being "nerds", Hacks/Hackers, they were sort of "lone wolfs" in their organizations. We were joking all day how you need to be a renegade to do data in the newsroom. Only that it is half-funny. Why is using data in a newsroom so difficult when the benefits are so obvious? Doing data journalism requires substantial know-how combined with a lot of personal motivation and energy, to overcome all the obstacles making it difficult to publish data driven stories.
 
That very day in Amsterdam led to thinking about an easier way to create charts. This then lead to the start of Datawrapper as a project, which was launched in 2012. All that is way back in time. But these roots help us to stay on a path: Make it simpler to publish charts. Datawrapper River is another step into that direction.
 
DDJ: How is the River different from comparable tools?

ML: The River is an extension - from tool to platform for exchange. Hopefully understood by many as an opportunity to get more data out to more people, already visualized. 
 
What we worked on are a number of features, specifically created to ease the exchange of charts between sources and newsrooms. Its part of an evolution towards better usage of data. In the past years we've seen a number of efforts towards that goal. Think of the data stores created by big sources like the World Bank, FAO Stat. Think of the many open data portals around the world. Quartz Atlas, not to forget. Other projects, which did not reach threshold.
 
Datawrapper River assumes that exchanging the chart or map should as easy as possible, without sacrificing quality over quantity. But to get there details are important. For example: Official sources gladly give you the data, but they ask for an attribution in return. News organizations, on the other side, do not like to re-publish content from another source with the external logo or as a package - that is always a looming conflict with core values.
 
 
Image: The River.
 
Some benefits are unique to Datawrapper, because we are deeply rooted in the news industry. Many newsrooms already have custom layouts in Datawrapper. If a chart is shared via the River, it comes in the basic layout. But it will automatically change to the newsroom layout once reused.
 
DDJ: What other specific benefits does it offer journalists?
 
ML: It's a new option to find relevant data and use it in your next article, right away. One click. This is not the only way in which journalists can use charts, but one that is underutilized. You can do a custom project, including coding, design for big stories. But then you need a data team and time. Another approach is to create a culture of good charting practices, my example would be what they do at The Economist, The Financial Times or "Neue Zürcher Zeitung" - still, you need specialists to do that and a budget. The option that is not used often enough is to use data in breaking news. I did an interview with David Bauer from NZZ last year - his goal to not have four, five or even ten big data interactives. At NZZ they use and create tools to improve 3000+ articles published over the year. Datawrapper River does that, on a potentially even larger scale and worldwide.
 
This is the key benefit of Datawrapper River: More data, more charts, in good quality, interactive and responsive for use in breaking news. In a typical shift of the day there is not time for big analysis, the task is to be accurate, to the point and be very fast. In this way, Datawrapper River is something new. Think of it as a wire service for charts and maps. Recurring data such as unemployment, crime, traffic and so on can come in directly usable visualizations this way. No need to download, prepare and upload one and the same dataset again.
 
There are some additional benefits: The River will help you to find data. There might be a chart which is a bit older and leads you directly to the source to create a chart yourself. And, finally, it gives you a steady stream of inspiration how to use charts for a wide variety of topics.
 
DDJ: How does it complement the original Datawrapper tool?
 
ML:  It is an extension of the tool - the main point being that we extend into a much wider user group in journalism. Out of 100 journalists working in a newsroom, there are usually no more than three or four experts for data. Ideally it's a data team, like what they have at the New York Times, Guardian US, La Nacion and so on. Three or four? These people are usually flooded with work and projects. We hope that through Datawrapper River the use of data and visualizations will spread further. Much further, essentially to a point where every journalist can use data, every day.
 
Explore Datawrapper River here.
 

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