Other work ↓
During my time at MING Labs, I led the overall user experience of a geospatial tool for almost a year. Such a tool allows experts to plan with and evaluate potential natural hazards. My responsibilities included, among other things, feature maintenance, user research and testing, shipping, UX and UI design, and user data analysis. I worked in close collaboration with data scientists, the back-end and front-end teams as well as the management to align the business goals and development constraints with the design. Since this project is under NDA, I cannot share any designs or further information.
In the following, I will cover some basics of geospatial tools.
The goal of such data visualizations is to make information easier to read and understand by others. Therefore, choices of classification, simplification or exaggeration of features, and symbolization of objects must be made.
Visualization of such geospatial data involves not only the representation of features, but also the explicit, consistent, and precise definition and description of the geographic features of interest. Errors of this nature lead to error-prone maps, analyses, and decisions. The desired accuracy depends mainly on the background and goals of the users.
Tools such as the USGS Earthquake tool ↗ enable users to monitor and estimate event scenarios. This is of critical importance, especially if a user's data set is potentially affected. Therefore, it is crucial to inform the expert about risks in a timely manner. Equally, the correct visualization on the nature of the event as well as its possible scenario is crucial.
With such tools, the user can combine data to derive new sets of information. However, these data sets are often huge. This amount of information can rapidly overwhelm and add complexity. Therefore, the user is able to filter through the information and visualize only relevant data. Users can analyze various layers to calculate the suitability of a place for a particular activity.
With the description above I wanted to give a short insight into geospatial tools.
As I was asked to take the lead on such a geospatial project, I knew that what awaited me would be challenging, but at the same time very worthwhile.
Working on such a similar tool taught me how to work with complex data structures.
In particular, I realized the importance of aligning the design with the backend developers' requirements, especially when working with a tool of such high complexity.
I enjoyed collaborating with and learning from people from a myriad of disciplines. I also appreciate that MING Labs has given me so much responsibility and trust to be in charge of such a major project which I took over from my very talented former colleague Miguel Pawlowski ↗.