In 2019, despite fewer total crossings, the Central Mediterranean route was deadlier than any of the previous four years: more than one in 20 people migrating from Northern Africa to Europe on this route died at sea. Combining graphics, sonifications and analysis, our project presented this data in the context of efforts from different governments to stop Search and Rescue (SAR) missions in the area. By reconstructing different vessels’ historical operations, we could show that political decisions led to a decrease in NGO-run SAR vessel presence. We put the increased death rate into a context no data existed in before.
As a student project, it did not have a large reach or impact. However, we received feedback that it had inspired fellow students to use simple tools in ways they had not thought of before, especially in increasing the accessibility of data visualisations for blind consumers.
As offered in the Sigma Award Rules, we would like to be considered for a “Young Talent” prize (but couldn’t find a designated field to indicate it in this online form)
We retrieved data on the operational status of vessels for each month from January 2014 until December 2019. Sources included news reports, position data from a marine position data portal, reports from the European Union Agency for Fundamental Rights, updates from the NGOs’ own websites and social media posts featuring information or images of the vessels in question. For data on numbers of crossings and deaths, we scraped numbers from the IOM’s missing migrants dashboard.
Using D3.js we created graphs of both the deadliness figures as well as the monthly numbers of vessels by operational status. The latter we also translated into a data sonification instead of just a visualization, which we created with TwoTone and added annotations with a voice-over. Also, using Adobe Illustrator we created illustrations of each SAR vessel, based on photographs and scaled to size using marine registry information about vessel sizes, to create a gallery of all ships that were active between 2014 and 2019. Lastly, we created a custom map of the area with Adobe Photoshop, based on Creative Commons map tiles.
What was the hardest part of this project?
A large part of the project was manually researching and gathering data on the operational statuses of the vessels. We created an original data set of monthly data on more than 20 ships covering five years, and did so by looking for records of each vessel in different open and closed sources, like social media and news reports, but also location data from a marine traffic platform.
Another challenge was finding ways to present the data in a non-visual way to make the content available to blind people and people with low vision, something that data journalism often fails to attend to. Firstly, we embedded the data underlying graphs as structured html tables for screen-reader users to scan themselves (embedded in the page as to avoid the extra-steps of downloading and having to open another file). The more complex line graph, which features two data rows and annotations for historical context, was turned into a data-sonification with voice-over. We also included the quite detailed annotations of the linechart as a text-based timeline.
Because (for us), it wasn’t possible to include the information for screenreader-users into the layout with visual graphics, we decided to provide two separate versions of the website – one with visuals, and one optimized for screen-reader users. As visual hierarchies of elements, e.g. by vibrant colors, don’t influence the order in which screen-readers translate the content of a website, it was important for the element which should be read first to sit (discreetly) at the very top of the website. These things we figured out through an iterative process with constant feedback from our team member who uses a screenreader, and we would love to see this kind of process be a normal part of developing projects in the industry.
What can others learn from this project?
This project shows that data journalism should not limit itself to reporting statistics that are ready and openly accessible, but that there is value in gathering data and creating relevant datasets ourselves if needed. It is also an example for expanding the idea of data journalism beyond data visualizations, including other forms of representation like sonification and audio narration, which is currently hardly seen outside podcasts. Lastly, we think it shows that even with very limited resources and skills (as we were just a group of three students on our first data journalism class with no organizational support from a newsroom) it is possible to communicate a complex topic in an interesting and engaging way, when using tools creatively – as we did with including decorative-informative illustrations and the sonification. The project also shows that where there is a will there is a way – and even without any resources or examples of screenreader-accessible graphics we managed to find solutions by researching, improvising, testing and iterating.