We develop open source software tools

Bird migration flow visualization

JS An interactive flow visualization of bird migration as detected by weather radars. Inspired by air and developed for the European Network for the Radar Surveillance of Animal Movement (ENRAM). See Shamoun-Baranes et al. 2016 for a paper describing the visualization. It was also used to visualize bird migration over Europe for Nilsson et al. 2019 (download movie).

Website Source code

CartoDB visualizations

CartoDB See our blog posts on how we have visualized bird migration and tracking data with CartoDB.

Checklist recipe

R The checklist recipe is a template GitHub repository for standardizing thematic species checklist data to Darwin Core using R. It contains all the ingredients to make data standardization open, repeatable, customizable and documented. The checklist recipe won the 2018 GBIF Ebbe Nielsen Challenge and we use it ourselves for the TrIAS project.

Documentation Source code


JS CROW is an online tool to visualize birds detected by weather radars. It pulls real-time open data of the Royal Meteorological Institute of Belgium (RMI) and visualizes it in the browser.

Website Blog post Source code

ENRAM data repository

Python The ENRAM data repository provides access to vertical profiles of birds (vp) data for Europe, which are used in radar aeroecology studies. The data are generated by vol2bird from polar volume data of over 100 weather radars in Europe and archived automatically on Amazon S3.

Website Source code


Python Vespa-Watch is a website where citizen scientists can submit observations of Vespa velutina, an invasive species in Belgium. The data are automatically synchronized with iNaturalist for verification and used to manage the spread of the species.

Website Source code


YAML Whip is a human and machine-readable syntax to express specifications for data. We use it with the pywhip package to document and test if data provided by our partners meet the necessary requirements for publication. See Van Hoey & Desmet 2018 for a presentation.

Documentation Source code