Data is important for us to understand the impact of climate change on Antarctic and Southern Ocean ecosystems. But it is not until we visualise this data that we can uncover patterns, better understand complex data, and gain valuable insight about the system we are trying to study.
The SCAR EG-ABI group is looking for a great piece of data visualisation that will help us share with the public the impacts that climate change is having on Antarctica and the Southern Ocean. We want to translate data into figures that are easy to understand and that move people to take action about protecting Antarctica.
Submit your best data visualisation piece to our competition for the chance to win prize money and get it featured in our social media channels.
- Get a team together. To encourage collaboration, teams must be at least two people.
- Create an infographic style graphic that can be easily shared in social media.
- We are looking for an aesthetically pleasing graphic that conveys a powerful message about climate change impacts
- You can use any dataset about Antarctica and the Southern Ocean, this includes remotely sensed data, in-situ observations, or model outputs.
- You can create your graph using any programming language, or editing software. However, the data analysis portion must be included with your submission.
- If text is included in your submission, it must be in English. You are welcome to make a submission with text in Spanish or French, as long as you also include an English translation.
- First prize: USD$600
- Second prize: USD$300
- Third prize: USD$100
- Clarity of message: does the submission use Antarctic/Southern Ocean data to convey a clear message about the impacts of climate change in this region? (weighting 30%)
- Design aesthetic: does the submission have a pleasing design? (weighting 30%)
- Multidisciplinary: does the submission convey the multidisciplinary nature of Antarctic/Southern Ocean science/policy work? (weighting 20%)
- Accessibility: does the submission use inclusive design decisions to aid accessibility, and consider equity in the representation of different people or groups? (weighting 20%)
- Dr Stephy Libera (Université catholique de Louvain, Belgium)
- Dr Patricia Castillo-Briceño (Universidad Laica Eloy Alfaro de Manabí, Ecuador)
- Dr Peter Morse (University of Tasmania, Australia)
Ensure your data analysis/visualisation code is available in a public repository on GitHub or similar.