I have previously written that I consider working with data part of a good investigative journalism. The inevitable further step is the ability to represent them in a way easily understandable by the reader.
Fortunately, and unlikely a decade ago, the web is plenty of useful tools that can accomplish this target for different kind of users expertise.
But let’s try to start from the problem. Let’s say we want to visualize a specific kind of data, like the ecological footprint of every country in the world. To make sense of the data that we are going to look at, we need to picture them in a way the state’s different levels can be compared with each other.
This is what my final work looks like, after had experimenting with the software Tableau Public.
Asking why I have embedded an image rather then the actual infographic?The reason is explained in this post. What I have tried to do here is a sort of infographic which aims to make sense of the data collected in an indipendent way. In other words I have embedded some text to describe what is visualized, so that the user have the chance to understand immediately of the figures.
Would it make sense to embed this entire work in a blog post? In my opinion absolutely not, because, having done this work for a course about infographic, it can be sold alone. But the versality of tableau allows to resize the infographic from the I-pad “landscape format” to a “medium blog post” one, and to eliminate the written parts.
What we firstly need is the raw data in a spreadsheet. I have found them in the United Nations Development Programme website, where there are a lot of interested indicators worth to work on. And in case you want to assemble different kinds of them in one spreadsheet to see any correlation, like for instance between the GDP per capita and the gender inequality.
Downloaded and cleaned the spreadsheet, it is all about following the instructions of the staff in this video.
The good
creative versatility: with Tableau you can create a dashboard, that is what the viewer actually watch, assembling different visualisations tools, like charts, map and scatterplot in the same context, without just embed them separately in a website.
multiple dataset: one workbook support as many dataset as you need, even if it is more likely to get confused among multiple pages and field names.
The bad
a bit fussy: during the project I wasn’t often able to visualize what I needed correctly because the values weren’t set in the right format. With a bit of trial and error I made it, but sometimes wthout really know the reason.
The ugly
my data management knowledge: what I really wanted to do was a filter based on continents, but I was’t able to insert a continent columns near the country’s names. With my actual knowledge this had would mean to write near every country’s name the specific continent manually. Unthinkable for more than 170 countries.
Any idea useful to solve this problem?
Making That Step 