This week, Operation Fistula (as part of the #Viz5 initiative) provided a dataset that looks at female genital mutilation (FGM) in Tanzania.
What is Viz5?
The ultimate goal of Viz5 is to create a space where data advocacy and insights meet impact.
This work seeks to ignite a data advocacy effort with the power to not only raise awareness of
extreme gender inequality, but also catalyze global action to end it. Viz5 is led by Operation Fistula, with #MakeoverMonday and Tableau Foundation operating as critical partners.
FGM in Tanzania
The theme for this month's (and this week's) Viz5 initiative was FGM. The World Health Organisation describes FGM as “all procedures that involve partial or total removal of the external female genitalia, or other injury to the female genital organs for non-medical reasons".
In Tanzania, approximately 10% of women aged 15 to 49 report having undergone FGM, but prevalence is much higher in the Mara region at 32%. The prevalence of FGM varies greatly by ethnic identity and within Tanzania these procedures are predominantly performed as a component of girls’ social initiation. Some groups, such as Kuria and Maasai people, have historically performed these procedures, while most others have not.
Hope for Girls and Women runs two safe houses in the Butiama and Serengeti Districts of the Mara Region of Tanzania, which shelter and support those fleeing FGM, child marriage, and other forms of gender based violence. You can read more about this month's Viz5 and download the supporting data and documentation here.
The original viz supplied was fairly simple in its analysis.
What I liked
- It's clear FGM is the largest reason why girls/women are admitted to the safe houses
- I can see there is a spike in cases around the end of the year
- It's clear that there is an immediate need for clothing when the girls/women arrive at the safe houses
What could be improved
- More context to the background of FGM and situation in Tanzania
- Pie chart has five sections, an alternative viz would be better
- Labels can be added to the bar chart as well as an explanation saying multiple needs may exist per individual on arrival
- A narrative explaining each visualisation would help provide more context
I wanted to take a more simple approach this week and focus more on storytelling. It's an area I'm sure we can all become better at.
I drew out a skeleton for the story that went
- What is FGM?
- The background of FGM and the initiative(s) in Tanzania
- How do girls/women arrive at safe houses?
- Who are they?
- What do we know about them?
- What support do they need and what are the recommendations?
- What organisations are involved?
The background image was created in Figma.
I wanted each part of the viz to have its own space and I wanted them to be spaced out. Admittedly there was a lot of going back and forth with Tableau and Figma as I built the visualisations, as some needed more space than I had initially allocated and some needed less.
I used the supplied spatial file to join to the dataset to produce the map.
Spatial files come with a field called 'Geometry'. Drag the 'Geometry' field into the Details pane to render the map.
I kept all other visualisations simple with bar charts or line charts for fear of losing emphasis on the story.
The text was taken from the supplied document in the dataset and I added some commentary based on the insights generated.
A table was added to show the details of all 851 girls/women recorded in the dataset. As you can see, it was difficult to put all the fields into the space I had on the dashboard so the headings for the measures are not readable. This viz was placed into a container and hidden using a show hide button.
Finally, I added a filter menu and a table to provide an alternative view of locations than the map.
You can interact with the viz below or view on my Tableau Public profile.