dataviz

EDJNet has recently released the first pilot version of “Mapping diversity”: it shows for the main city in each of Italy’s regions how many streets are dedicated to men and women and includes details about who these streets were dedicated to. In a visually impressive format developed by Sheldon.studio with text and analysis by Alice Corona, it highlights that many more streets are dedicated to men than to women, and that many of those women are Catholic saints or other religious figures.

This post has originally been published on Medium by EDJNet A different visual approach to associate likelihood of occurrence of a given event to the lived experience of people viewing the graph. In their 2007 book “The illusion of certainty: Health Benefits and Risks”, authors Erik Rifkin and Edward Bouwer addressed a number of aspects related to the communication of risk to individuals and broad audiences, arguing that adequate communication of risk, including on the uncertainty embedded in risk assessments, is fundamental to personal and collective deliberations.

This post presents a data exploration tool developed by EDJNet. If you have a spreadsheet with longitude and latitude columns and would like to have a look at those data on a map or associate them with administrative units across Europe, you may well find this tool useful. You can try this online, or check out this screencast for an overview of its main features. The interface is available also through the R package latlon2map.

In this video, I point at some of the issues that characterise data grids and that may generate misunderstandings. In the video, I mention how gridded data can be generated via satellite imagery and machine learning techniques. Of course, such data can be generated also via other means. References This video is based on the data used for in this interactive web interface, presenting municipality-level data for most European countries:

A structured approach and a new R package to deal with a recurrent question

Among the many debates that follow elections, there is one that usually gets most attention among data journalists and people with an interest in data visualisation: electoral maps. This is not a purely aesthetic debate, as both newsreaders and political pundits make sense of election results through these maps, reaching often debatable conclusions. A common one, for example, is the idea of a “country divided” as highlighted by Giuseppe Sollazzo in a post focused on maps published after the 2018 election in Italy.