From Data Sets to Data Visualization: Tanzania Dashboards

September 19, 2016
Diego Andres Dimunzio, Mark Irura
Innovation, Open Data

In an earlier post, we shared the context and intended purpose of the Tanzania Sectoral Dashboards; in this post, we dive into the technology behind the data visualizations.

Seeking to put the Principles for Digital Development into practice, we built the Tanzania Dashboards using open source tools and frameworks, which reduces the total cost of ownership. The dashboards pull data dynamically from the Tanzania Open Data portal APIs, and uses a powerful combination of Angular, ReactJs, CSS, and HTML for the user interface. For mapping, they use Leaflet and Open Street Maps. The resultant source code (Water, Education and Health) is also open for download and further extension.

<p>Key libraries and technology used to build the dashboards</p>

Figure 1: Key libraries and technology used to build the dashboards.

The technology stack was chosen based on needs and functionality. In the case of education, since there was already an application in place that what we had to enhance, the whole development was done in AngularJS; for the other two dashboards we had greater flexibility to choose the stack.

From a user experience perspective, we had determined to include both georeferenced visualizations (maps) and charts as part of the dashboard. In maps, clusters are a useful way to show data points, especially in maps with high datapoint density — the Water Dashboard’s waterpoints are a strong example of this. After some research, we found Prune Cluster, useful because it (i) permits a category to be specified for the markers, after which (ii) a small object representing the number of markers for each category is attached to the clusters. In this way, you can create cluster icons adapted to their content — in our case, it helped us to show water point status for a group of the points at-a-glance.

<p>Waterpoint Map with Prune Clusters</p>

Figure 2: Waterpoint Map with Prune Clusters.

When developing charts, our goal was to create powerful tools for data analysis — we also needed to use a specific library, based on the government’s requirements. For these reasons, we selected the Highcharts library. Both the charts and maps have been optimized for low-bandwidth environments.

<p>Tanzania Health Dashboard charts</p>

Figure 3: Tanzania Health Dashboard charts.

The dashboards are built on open data released by the Government of Tanzania, and read the raw data published on the Tanzanian Government Open Data Portal (ODP). The data are displayed on the map at the most disaggregated level possible — some datasets from ODP only contain data that is aggregated at the region, district, or ward level.

Data sources for each dashboard are as follows:

In some cases, the dashboards use data that has been cleaned or merged with other data to create new datasets — but even in these cases, the data itself draws exclusively from open data released by the Government of Tanzania. All data is available for download in machine-readable format, with a license that encourages re-use.

However, it is important to note that the dashboards are as good as the raw data sources which drive them. Consequently, an important consideration for all the dashboards should be the provision of timely and complete data by the sector ministries. We are hopeful that planned trainings and sensitizations carried so far will increase the uptake. Naturally, timely updates and relevance to the latest approved datasets will stimulate demand through increased interest and use by end users.

In summary, we hope these dashboards help government and the public quickly sift through the government’s open data, and make it easier to understand, analyze, and use this information. But technology is just the first step in a data-driven decision-making chain: it is now for individuals to use their judgement and leadership instincts to act upon this information to progress toward national goals. We look forward to championing the Government of Tanzania’s successes, and working with our partners DataVision International and the World Bank again in future.

Share This Post

Related from our library

The State of Data in DG’s Work

As we review our strategy, we plan to share here much of what we’ve learned through programming in more than a dozen countries – from our work and from our excellent partners – about the state of data in agriculture, tobacco control, open contracting, and the extractive industries. For each theme, we’ll explore who are the key data users, the decisions they make, the most important data gaps, and the crucial risks of data (mis)use. Here we share previews from some of our flagship programs.

October 27, 2020 Extractives Management, Global Data Policy, Health, Open Contracting and Procurement Analytics
HIV/AIDS Response Through Youth-Led Community Mapping in Côte d’Ivoire

With support from DCDJ, local youth in Côte d’Ivoire organized a successful mapathon to get community resources, landmarks, and risk zones in Daloa – particularly those relevant to young people – on the map. Through the process, they acquired new skills including OSM tracker to develop map layers, how to collect local data, and how to communicate results stored in a new database developed through the program.

September 23, 2020 Health
Building Procurement Back, Better

As governments look to “build back better,” we can expect an influx of government spending to stimulate the economy, and a shift in priority goods and services to purchase. While the world transitions from emergency response to recovery, governments’ focus will shift from using technology to procure other products, to procuring technology products themselves.

September 18, 2020 Open Contracting and Procurement Analytics