Reflections about designing geospatial data visualization tools

Design Lead for a B2B geospatial web application in the area of risk management.

The average global surface temperature between November 25, 2001 - December 2, 2011. © NASA Earth Observatory (NEO)

For almost a year at MING Labs, I was in charge of the overall user experience of a geospatial tool. Feature maintenance, user research and testing, shipping, UX and UI design, and user data analysis were among my responsibilities. To align the business goals and development constraints with the design, I worked closely with data scientists, the back-end and front-end teams, as well as management.

Since this project is under NDA, I cannot share any designs or further information. Below, I briefly write about the domain I was designing for.

Visualization of a storm

Assessment of risk areas

In recent years, it has become clear that, as a result of climate change, weather-related damage has increased dramatically. Therefore, it is critical for experts to quickly identify and assess areas of risk and monitor events that may affect their data sets. Those data sets may include, for example, residential and industrial areas.

Climate hazards include all kinds of disasters such as wild fires, tsunamis and floods. Rising sea levels, for example, will put many properties at risk, particularly in the Nordic countries. For example, rising sea levels will lead to Experts must be able to calculate risks of their data sets.

Such geospatial tools enable experts to:

November 8, 2018. The Camp Fire in California was one of the most destructive wildfires in Californian history. © NASA

Visualizing datasets

Experts frequently work with multiple data sets containing a large amount of data. As a result, an appropriate level of abstraction must be found without compromising the data's accuracy. When working with large data sets, it's critical to know what level of detail experts require in order to process the data and achieve their goals.

Zoom in view of a dataset
Zoom out view of a dataset

Visualizing events

Natural disasters, for example, can be visualized using geospatial tools, as shown in this example. Experts may want to focus on a specific type of event, and thus be able to filter out those they need to pay attention to: The earthquakes depicted below can be filtered and categorized based on parameters such as location, time, magnitude, and so on.

Selected earthquake
Earthquake overview

Filtering datasets

It is crucial for the expert to use and process only the information they need in the given moment. Therefore, experts can mark the segments they want and use them as filters to combine and process only the data within those segments.

Marked area
Show exposure of events which are in marked area
Afftected data set
Show exposure of events which are effected by the earthquake


• Alignment with stakeholders is crucial. I realized the importance of aligning the design with the requirements of the back-end developers and management, especially when working on such a complex tool which involves many stakeholders.

• Working with scientists, engineers, front-end and back-end developers required a certain level of knowledge that I had to acquire quickly, especially in order to share a common language and understanding of the demands and work of each colleagues.

•I learnt how to work with complicated data structures and how even minor differences in their representation, as well as inconsistent definitions, can result in analyses, and conclusions that are extremely critical and error-prone. Being mindful of details is key!

• Leading the design of such a big project as a young designer can be very frightening. I learned to trust in my abilities and to make important decisions in a confident and quick manner.

I took this project over from my very talented former colleague Miguel Pawlowski.