Today we are adding a very simple and fast way to create and publish maps. Another new feature is the of Datawrapper Team, as an effective way to use this tool professionally.
There is a bit of a backstory here, stretching back to mid-2012: When we first saw Kartograph, the map library created by Gregor Aisch, we surely wanted this to become a part of Datawrapper. We wanted to enable everyone to create a meaningful map, in short time – the same we did for basic charts.
But simplicity is hard. It took a lot of work to get this point. Gregor joined Datawrapper as the head developer in 2012. We launched Datawrapper 1.0 in November last year and kept on developing, so today we reached Datawrapper 1.7.
Usage growth for Datawrapper 2013
As a result, we saw incredible usage growth in the last twelve month. The number of “chart views” jumped to roughly 45 million in 2013, up from about 2,5 million in 2012.
Many of the leading newsrooms in the world are using this tool. We saw charts “created with Datawrapper” on websites like the Washington Post, Der Spiegel, The Guardian, Der Standard, Tagesspiegel, Neue Zürcher Zeitung and many others. Usage is worldwide, strongest in Europe, but gradually spreading to the US, Australia, New Zealand and sites in Asia, such as Nepal.
A recent addition has been the “secret data journalism project” by the Trinity-Mirror Group, by the name of Ampp3d. They did not even call us, just started to use Datawrapper cleverly, changing the colors as needed and quite cleverly just skipping the headline/pre-text feature to have the charts nicely embbeded into their stories.
This is well beyond what we hoped for when we started this.
Here are maps…
Today we are releasing Datawrapper 1.7 with maps as the big new feature. It is labeled beta, as we will add more maps shortly and some additional features. The concept though is the same as for the charts: Datawrapper is designed to create correct, responsive, embeddable visualizations in very short time. This is our main goal: To help journalists working under deadline adding data to their stories.
Quick guide: How to create a map with Datawrapper
Note: If you want to just test the map feature, we now have one sample dataset just for testing. Just log into Datawrapper to see how it works.
1. Find data
First of all you need a dataset with one row having geo information. These can be country names for example. Datawrapper will automatically read country names, etc. and create a choropleth map in just a few steps. Each map in Datawrapper is designed to accept many of the standard region keys. For the world and continent maps, each country can be addressed using the two and three-letter ISO key. In addition country names are also accepted, in any language supported by the map. You can even mix the keys, so if one country name is not recognized by Datawrapper you can just insert the one country code without having to change your entire dataset.
2. Upload into Datawrapper
Tip: When you click on the upper column (A, B) you can assign a specific format to the data. The map can display both textual and numerical data.
3. Select “Maps” in the next step
In the second panel (“Refine the chart”) you choose the base map from the list of currently available maps. Then you can select column that stores the geo IDs (map key column) as well as the column that contains the data to be shown on the map (data column). Datawrapper will automatically detect these columns for you, but in some cases you might want to adjust them to fit your dataset.
4. Change the color with one click, highlight important elements
Optionally you can also adjust the colors used in the map, or alter the way the data values are classified into the color buckets. You will notice that changing these parameters has a great effect on the overall appearance of the map (and how the story is perceived!). It’s definitely worth taking care of your choropleth maps.
Using the existing highlighting feature you can add simple labels to selected map regions. We recommend to keep it simple and just focus on the regions most important to your story. Keep in mind that maps can get too crowded with labels very easily.
That’s it. Hit publish and you are done. Let us hear your comments.
Next steps for maps
This is only the start. In the future we want to add more maps of important world regions and countries. One thing though: In order to have maps as part of customized layouts, there is a bit of customization work to be done. On the other side, we can now offer local maps, which would cover just one city, one region, etc. Creating those maps for individual users will be covered by costs per hour, as we did in the past for customized layouts.
Welcome Datawrapper Team
During 2013 we already offered customization services for a fee. In order to create a custom layout, add specific modules, more data input options and so on, we so far offer Datawrapper Pro. This is a fully dedicated server, where we do the service of installing and maintaining Datawrapper for just one brand. For all larger companies interested in adding capabilities for data-driven visualization this is the best and most customizable option. The price per year is €8000 Euros, with unlimited chart views, unlimited users. The only extra costs are the creation of custom maps (though five maps are already included) and specific modules created just for one client, such as workflows from web to print. These are charged based on the hours worked.
What is the difference between Datawrapper Pro und Datawrapper Team?
But not all newsrooms have such big plans. Or budgets. But would still like to use Datawrapper with customizations, maybe with an option to upgrade to Pro later.
This is why Datawrapper Team is the new entry level option for professional use of Datawrapper. Costs are €1200 Euro per year plus a one-time fee for a customized layout with multiple options at €800 Euros. The number of users is limited to five, additional users can be added at €120 per year per user. As with Datawrapper Pro we charge by the hour for other customization services, modules. Custom maps are created for €80 Euros per map, with rebates for higher numbers.
Here is a sample view on how Datawrapper Team works (The Guardian is just used as an example here). One big option is that teams can now work together in the future, share and open each other charts. This means that a growing archive of charts can be used by more widely, making updates of recurring data much simpler.
Customization services for Datawrapper will be managed by Journalism++ Cologne, the recently created local chapter of the network, with help and expertise from the growing group of data journalists and coders.
Contact us via firstname.lastname@example.org.
That’s it for 2013. This was intense, but fun. A big thanks to everyone helping us, using Datawrapper, giving advice, asking questions and caring for data.
See you again in 2014. Take care, get some rest.