#WildEye: Mapping wildlife crime

Category: Open data

Country/area: South Africa

Organisation: Oxpeckers Investigative Environmental Journalism, Earth Journalism Network

Organisation size: Small

Publication date: 28/01/2019

Credit: Fiona Macleod, Roxanne Joseph, James Fahn, Charlotte Schep, Mike Shanahan, Sara Schonhardt, Anina Mumm, Mark Hartman, Tristan Mathiesen, Paul Kennedy

Project description:

#WildEye is a pioneering geojournalism tool that, for the first time, provides access to consolidated data on wildlife crime in greater Europe. Developed by journalists for journalists, it aggregates and shares information on seizures, arrests, court cases and convictions relating to illegal wildlife trade. Journalists use the tool to look for data, patterns and trends, and #WildEye hosts a growing dossier of investigative reporting. It is also used by civic organisations, law enforcement agencies and policy-makers. Pioneered by Oxpeckers Investigative Environmental Journalism, #WildEye is partnered by the Earth Journalism Network, and is currently being replicated in Asia.

Impact reached:

We have seen significant successes in making wildlife trafficking data publicly accessible. By shining a light on the scale of illegal wildlife trade taking place, we have sparked the interest of other reporters, law enforcement, and organisations monitoring and investigating wildlife crime.

We have mapped nearly 400 incidents of seizures, arrests, court cases and convictions on the #WildEye map. These span the entire continent and record information on close to 100 different endangered species. 

We have formed ongoing relationships with organisations across the globe, including wildlife monitoring agency TRAFFIC, the Global Initiative against Transnational Organized Crime, the Wildlife Justice Commission and USAID. We have also interacted with law enforcement agencies, including Interpol, Europol and local law enforcement. 

More than 25 investigations have been published. These have been viewed and shared hundreds of times. Topics include an exposé of illegal tiger farms in the Czech Republic; songbird smuggling from Italy to Malta; the poaching of sturgeons in Romania and Bulgaria; the black market for parrot eggs smuggled into Europe from the Amazon; and how traffickers use the world’s largest reptile market to sell protected species. 

We met with journalists funded by our partners at Earth Journalism Network, and at convenings in the UK and Germany. Here, we trained them on how to use the map and workshopped story ideas that incorporated #WildEye data. 

In November 2019, we hosted a live webinar, where close to 30 participants from around the world received that same training, this time in the context of the updated #WildEye map. We looked at why Europe, and why now; explained to participants what #WildEye shows and taught them more about how to use the tool; and had a lively discussion on the difficulty of accessing wildlife crime-related data. Listen to the webinar here: https://oxpeckers.org/2019/11/talking-wildlife-crime/.

Techniques/technologies used:

#WildEye was built by developers using an open-source platform called Mapbox. This was customised to fit in with Oxpeckers’ style and to suit our needs as data journalists. 

#WildEye’s main feature is a map of Europe showing where law enforcement agencies have been involved in action against wildlife trafficking. Each case is identified by an icon that signifies either a seizure, an arrest, a prosecution or a conviction.

Move your cursor over any icon and a text box will pop up, providing detailed information about what products were seized, who was arrested, and how much they were fined, for example.

The tool includes a search function to help users filter information and find topics of interest. If you want to learn about the illegal trade in birds, for instance, simply type “birds” in the search box and you’ll get a host of results covering seizures, arrests, court cases and convictions involving that word.

Data is uploaded on Mapbox back-end via a Google spreadsheet that is updated on a weekly basis, sometimes more frequently. Methods of data collection range from scraping the net to obtaining reports from several dozen organisations who monitor wildlife crimes. We convert bulky reports into spreadsheets that can be analysed and added to #WildEye. By engaging with organisations such as TRAFFIC and the Wildlife Justice Commission, we have been able to access some of this data more easily.

What was the hardest part of this project?

Our biggest challenge has been accessing data – mainly because #WildEye is the first platform to collect, collate, analyse and make public data on legal processes relating to illicit wildlife trade in Europe.

We always knew that we were creating a tool that maps and makes the data public, but quickly came to understand why we were doing this when we hit dozens of roadblocks and had to fight to get information. 

This led to a lot of crowd-sourcing, scraping and meeting with organisations to give them a better idea of why this data should be accessible to anyone and everyone. It took some creativity and teamwork, but our efforts became clear each time a new journalistic investigation was published and when organisations working in the field started using the platform for their own research. 

Platform challenges included customising Mapbox templates to update data quickly and to show all data points properly and in full; adding a spiderfier functionality to Mapbox as the data sets increased (and the map began to look too busy); creating searchable tags and clickable menus; making it easier to add and access #WildEye data as a member of the public; and explaining how to use the tool as new users. 

These issues were solved by doing two things: first, we included the data manager in the tech-related updates and back-end functionality of the tool, and encouraged them to work closely with the developers. Second, we created a more community-friendly tool, which now includes user guides, direct links to adding and accessing the data, and a cleaner, more simplistic-looking map. These changes were supplemented by running a webinar to encourage users to experiment with the tool and provide feedback on its usefulness to their own work.

What can others learn from this project?

The main thing that others can learn from #WildEye is that making data on wildlife trafficking accessible is crucial in the fight against it. We cannot expect people to understand these issues if they cannot get information and read stories about them. 

#WildEye is a resource that was developed by journalists for journalists, and is a centralised platform used to tell compelling data-driven stories about illegal wildlife trade. 

We started by focusing on Europe because of its growing importance as a trafficking hub, and the fact that it is a source of wildlife products that are high in demand in other regions. Until now, there has been no single place to access information easily on efforts to crack down on wildlife crime on the continent. #WildEye addresses these gaps by  tracking the scale of Europe’s role in the illicit trade, and by helping journalists to increase media coverage of the problem.

By exploring the data, journalists can look for patterns and trends that can inspire new investigations. For example, why are there more seizures in some countries than others — is it due to more intense controls or to the preference smugglers have for certain routes? Why do so few seizures result in prosecutions and (fewer still) convictions? 

#WildEye is a fantastic customisation of open-source technology, which we hope encourages others – especially journalists – to test similar methods of visualizing large datasets of their own. We have been vocal about the tech-related challenges we faced throughout the creation of this tool during in-person interactions, on panels and in the webinar, and hope that others learn from our experiences. Making important data sets look good and easily accessible does not have to be difficult, and #WildEye is a prime example of this, within the context of data journalism. 

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