It’s Week 4 for Makeover Monday 2018 and already, I have been pushed to my data visualisation limits so far this year. The datasets have challenged me to work hard to find suitable story angles whilst keeping the vizzes user friendly.
This week’s dataset is looking at Turkey Vulture migration in North and South America from 2003-2011. When I looked at the data in the spreadsheet, it was definitely quite a shock to the system but knowing me, I love a challenge no matter how big or small it is!
Here is the original visualisation that was published in an article for the Royal Society Publishing:
What I like about the viz
- I love how I can see how the turkey vultures have migrated in terms of it’s return and outbound location.
- The minimal use of colour for the migration of turkey vultures helps to see where they have migrated from North America to South America.
- Appropriate use of a map in which you can exactly see where the turkey vultures are migrating to which country.
What could be improved?
- Remove the longitude and latitude axis as they don’t serve a purpose to the visualisation.
- What turkey vultures are migrating to South America or North America? Are they migrating more to Southern America or are they staying up North? It’s unclear what the viz is telling me.
My goals for this week
- As this week was another dataset that was centered around a map, I knew I had to produce another map-based viz.
- Start using Mapbox as a way of visualising mapping data rather than using the Tableau default map.
- When it comes to something I have no knowledge about, it does take me longer to come up with an idea to viz with. I usually sketch my vizzes before I build it in Tableau. However, with this dataset, it was really difficult to sketch the viz on paper.
- Keep the colours to a minimum and focus on one turkey vulture subject (e.g. Rosalie).
With that said, I really enjoyed Week 4 for Makeover Monday 2018 on turkey vulture migration. If I have learned something new every week, then it’s all the worthwhile when it comes to producing data stories for journalism!