CGA, headed by Wendy Guan, was established to support research and teaching across all disciplines at Harvard as they relate to geospatial technology and methods.

Geospatial data is invaluable to organizations to understand complex problems with regional components, such as climate, change, public health, or political conflict, for example. But accessing and analyzing geospatial data has traditionally required specialized expertise and the use of systems with exceptional processing power – blocking full utilization of geospatial data.

The Spatial Data Lab at Harvard has developed a no-code/low-code geospatial extension that makes geospatial data easy to access and understand. With KNIME, users have a platform that is intuitive and eliminates the need for specialist data science knowledge. It also enables non-data experts to become self-sufficient in the use of geospatial data

The Lab chose KNIME as KNIME is open source, offering zero start-up cost and making the solution highly competitive against costly alternatives. It is intuitive, making it easy for users of all skill levels to use. It can handle the processing challenges, performing complex geospatial analysis quickly, and it supports collaboration, making it easy for teams to share work, including with people from different domains.