Use IMF API to automatically collect relevant data soures Process data as needed Create metrics to define majority import (in this case which ever of the three countries the share of the imports are from) Combine geojson file with data so that there is a proper geospatial file with the neceesary information Creating visuals of the dataset Start to finish process in one Jupyter Notebook GitHub Repository

Define metrics: Availability = Bike Paths (km)/ Roads (km) Quality = ( Seperated Bikepaths / All Bike Paths )*100 Utilize API to collect data from OpenStreetMap Acquire appropriate shapefiles from the city authorities Clean and process data Create data visualizations and report findings GitHub Repository

This project expands on the work by Sewerin, S., Kaack, L.H., Küttel, J. et al. Towards understanding policy design through text-as-data approaches: The policy design annotations (POLIANNA) dataset. Sci Data 10, 896 (2023). https://doi.org/10.1038/s41597-023-02801-z. The POLIANNA is a dataset of policy texts from the European Union (EU) that are annotated based on theoretical concepts of policy design, which can be used to develop supervised machine learning approaches for scaling policy analysis.

This is a student-run workshop workshop session on the Leaflet package in R. equip attendees with conceptual knowledge about the leaflet package and some of its applications for geospatial analysis show attendees key functions and the basic steps to make an interactive map in R provide attendees with practice exercises as well as some further material that can be useful for the topic of this workshop Tasks involed: