Improving the Usability and Adoption of Digital Data Solutions: An Example for Researchers in the Digital Waters Flagship and PhD Pilot

Geospatial data are increasingly available openly online, and often they are accessible in multiple ways, including web application programming interfaces (API) by the Open Geospatial Consortium (OGC). However, researchers often continue to rely primarily on manually downloading datasets to their laptops for their daily research activities. This workflow has some disadvantages. For example, if the input data updates often, making sure that all the researchers working on the topic have the exact same dataset available is a manual and an error-prone process. The use of web APIs could provide help for various use cases but requires some IT knowledge that many substance experts may lack. 

To address this challenge, we developed a set of Jupyter Notebook examples designed to support researchers in accessing, exploring, and analyzing geospatial data from APIs in both virtual and local computing environments. The notebooks demonstrate and compare multiple approaches for directly accessing vector, raster, and point cloud data, as well as associated metadata records. We test the notebooks on a course for PhD students related to the Digital Waters Flagship by the Research Council of Finland and evaluate their effectiveness using a questionnaire for the course participants.  

With the proposed approach, we aim to lower technical barriers and facilitate the integration of distributed data into existing research workflows. Ultimately, these practices can support the creation of digital twins of water resources and contribute to intelligent and sustainable water management. 

 

Keywords: geospatial data, data infrastructures, Jupyter notebook, data space, technical barriers