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Data story visualisations
Visualisations are a key part of telling a data story. They let your audience see what the data conveys and lets them explore the data on their own.
The visualisation chosen should match the question you are using to create your story and the characteristics you discovered in your analysis as seen in the above image published in by PesaCheck.
In this lesson, you will learn:
- Narrative trends over time
- Surprising or counterintuitive data
- From details to the big picture
- Intersecting or diverging data
- Tracing flows
Narrative trends over time
Data stories often describe how conditions change over time. These stories can show the impact of long-term trends and highlight external changes that might impact those trends.
For example, this visualisation shows the change in the number of waterborne disease cases reported in Busia County in Kenya over the period of January 2019 to April 2020.
Surprising or counterintuitive data
Data stories can highlight surprising or counterintuitive results. A data story may provide evidence that contradicts and challenges common misconceptions.
For example, the highest prevalence of female genital mutilation cases recorded in Nigeria could be believed to be among those with a low level of education. However, the data shows that female circumcision was more prevalent among women with secondary or higher education levels.
Data stories can make comparisons between different groups or categories, and provide context to put information into perspective.
For example, the visualisation above published in this article gives a comparison of sexual assault victims by age, recording the changes in cases over time. Mirabel Sexual Assault Referral Centre in Lagos, Nigeria reports that most victims are aged 14-17 years followed by ages 6-10 years and 11-13 years.
From details to the big picture
Data stories can provide a larger context for a smaller area focus or vice versa. This approach is especially helpful for comparing local data to a larger geographic area. Maps that allow users to explore their own states or neighborhoods can be particularly effective.
In this visualisation above for a story addressing Inadequate PPE supply, the number of doctors, nurses, pharmacists, and community healthcare workers in Africa are mapped. Readers can hover over an area to see details in any country.
Intersecting or diverging data
Data stories often unfold when two or more sets of data intersect or diverge.
Intersecting data refers to an instance when two or more sets of data meet and cross at a point in time. On the other hand, diverging data in an instance where two or more sets of data take different directions. Your audience will want to know why these changes occur. Common examples include political opinion, life expectancy, and wages.
This visualisation shows the relationship between the number of people affected by key natural hazards in Kenya over time, using data from the World Bank Climate Change Knowledge Portal. Natural hazards such as epidemic and drought intersect between 1991 and 1994. Drought diverges from the rest of the natural hazards from 1997 to 1999.
Data stories can convey complex data relationships that would be almost impossible to make sense of otherwise.
This is especially true for flows of commodities, such as goods, money, or information between multiple sources and destinations.
This example showcases aid inflow into Zambia from 2000 to 2013, using records from AidData. It makes it easy for audiences to see the aid between particular countries and regions, and if one hovers over a particular flow line they can get information on the country and amount of aid donated.
Test your knowledge
Visual narratives with data
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Question 1 of 1
Which one of the reasons listed below are not given for telling stories with data?CorrectIncorrect