Exploring the visualization process: how to visualize child malnutrition?

In our previous blog post, we introduced our topic about child malnutrition with a focus on Pakistan. The ultimate goal of this project is to create three relating visualizations in order to tell the important story of child malnutrition. Specifically, this blog could be viewed as a journey that eventually leads to (1) an interactive (clickable/zoomable/filterable) visualization , (2) an interactive infographic , and finally, (3) an animated infographic video.

The starting point for each separate visualization are the several datasets provided by large international organizations such as UNICEF World Health Organization (WHO), United Nations and the Food and Agriculture Organization. The challenge is to translate these complicated datasets into understandable and attractive visualizations. There are several tools available for this visualization process, such as infogr.am, piktochart.com, Tableau and Google Fusion Tables. Exploring the benefits and disadvantages of these tools is another stage in this project and will be the main topic of this blog post.

The datasets: looking for interesting visualization material

The first two datasets we encountered with regard to child malnutrition were provided by UNICEF, partly in cooperation with the World Bank Group and WHO. The first dataset consisted of stunting disparity rates in children under five for different countries and areas, making a distinction between rural and urban areas of residence. The data can be used for making comparisons between Pakistan and other countries or parts of the world. Secondly, we explored a very extensive dataset on ‘child malnutrition estimates’, including overweight, underweight, stunting, wasting and severe wasting. Besides exploring the different subtopics of malnutrition, the different survey years provide the opportunity for creating a timeline.

Direct links to our first two datasets:
• Stunting Disparities by Residence and Wealth Quintile
• Joint Malnutrition dataset from UNICEF, World Bank and WHO

Starting the visualization process

With this information in our minds, we started playing around with the previously mentioned tools. For the interactive infographic, it was decided to use infogr.am and piktochart.com. These tools are both well known and require no specific skills from the user. As a first draft, we created different visualizations by using the two datasets from UNICEF. Both the bar- and line chart reveal information about Pakistan in relation to malnutrition. As can be seen in both visualizations, stunting prevalence is a serious problem in Pakistan. High standard deviations from the WHO Child Grow Standards, especially with regard to underweight and stunting, reveal that Pakistan is highly affected by child malnutrition. The map of South-Asia has not been combined with data yet, but is a very interesting tool to visualize comparisons between Pakistan and other related countries.

infographicwordpress
Exploring different tools for infographics in Piktochart

For the interactive visualization, we experimented with four different tools, which were: Alteryx, Tableau, Gapminder and Google Fusion Tables. Eventually, it was decided to stick with Tableau, mainly because of the user-friendly working environment and the numerous visualization possibilities. At the moment, we are working on an interactive visualization about child malnutrition across the world. Again, we are using the two previously mentioned datasets of UNICEF and, additionally, we are combining these data with the GDP’s of several other countries. In that way, we are trying to reveal causal relationships between child malnutrition and other important developments in society, such as the economic situation.

printscreen tableaux
A snapshot of our current activities in Tableau

What’s next?

We keep on working and experimenting with visualization tools in order to tell an interesting story about child malnutrition and Pakistan in the end. However, during our first steps in the visualization process we noticed that more data on the subject is a necessity. In our next blog post, we hope to inform you about our progressions and come up with new facts and visualizations!

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