Mastodawn

We wrote a small piece on our open #Erasmus #StudentMobility data for a Finnish GIS professional magazine, Positio, with @miladmzdh, Oula Inkeröinen and Olle Järv. It is in #Finnish though.

It just came out:
https://positio-lehti.fi/2025/05/avoimella-opiskelijavaihtoaineistolla-uusia-nakokulmia-euroopan-aluekehitykseen-yli-2-2-miljoonan-opiskelijavaihdon-geokoodattu-aineisto-euroopasta-saatavilla/

#GIScience #Paikkatieto #Positio #Opiskelu #Tutkimus #Tiede #Vaihto #Research #AvoinData #OpenData

Avoimella opiskelijavaihtoaineistolla uusia näkökulmia Euroopan aluekehitykseen - Yli 2.2 miljoonan opiskelijavaihdon geokoodattu aineisto Euroopasta saatavilla! | Positio

Ihmisten liikkuvuus on saanut paljon huomiota paikkatietoalalla viime vuosina eikä syyttä. Liikkuvuutta kuvaavia aineistoja käytetään laajalti eri

Positio

Milad Malekzadeh May 12

Ever wish you knew who already collected the GPS data you need?

We propose OpenGPS—a platform to share, store & process human mobility tracking data.

🌍 Phase I: metadata sharing, find out who has what
📦 Phase II: data storage & sharing
🧠 Phase III: privacy-aware cloud-based analysis tools

✅ Prototype already live

With @jedalong, @udemsar, Katarzyna Sila-Nowicka, Vanessa Brum-Bastos, Jinhyung Lee & Hui Jeong Ha.

📄 Paper: https://doi.org/10.1016/j.dib.2025.111603

#OpenScience #GPS #HumanMobility #OpenGPS

Milad Malekzadeh Apr 17

Tuomas Väisänen 📼🧟‍♂️Apr 17

✨ NEW TOOL FOR #MOBILITY DATA #DATAVIZ ✈️🚚🚗🏃

Do your visualisations of origin-destination matrices look like a mess of criss-crossing hairs? Maybe you could benefit from our #EdgeBundling tool by me, Oula Inkeröinen, @miladmzdh and Olle Järv!

🛠️ The tool: https://doi.org/10.5281/zenodo.14532547

This tool is an output from the #MobiTwin project funded by the #EuropeanUnion through the #HorizonEU programme.

Edge-bundling tool for regional mobility flow data

Edge-bundling tool for regional mobility flow data This repository hosts the scripts to perform edge-path bundling (Wallinger et al. 2022) for flow data. It's primary use case is to support visualization of complex mobility data, and has been used to bundle human mobility flows across NUTS regions in Europe. The tool's inputs are two CSV files, one for point feature data and associated coordinates, and another for flows (edges) to be bundled. After bundling, the tool outputs a GeoPackage file. The script expects the data to be in WGS84 coordinate reference system. The scripts in this repo are repurposed versions of the original scripts written by Peterka (2023). The updates to the original code aim to make the code more usable for analytical purposes. This tool is an additional output of the Mobi-Twin research project. Requirements The scripts within the repo require Python 3.10 or newer version with the following packages: pandas geopandas tqdm shapely On top of these Python requirements, the script expects the input CSV data (centroids and edges) to have a certain structure. Data structure for input files Centroid file | ID_COLUMN | X | Y | | ---- | :----- | :---------- | | Unique identifier for centroid (e.g., NUTS code) | X coordinate (WGS84) of the centroid | Y coordinate (WGS84) of the centroid | N.B.: The ID_COLUMN in the above is an example name, use the column name you have in your data. Edge file | ORIGIN | DESTINATION | OD_ID | COUNT | | ---- | :----- | :---------- | :---------- | | ID code of origin | ID code of destination | ID made of origin and destination codes joined by an underscore (_) | Integer/floating point number of flow strength | N.B.: The ID codes of origins and destinations have to match the IDs of your centroid file. Usage Clone this repository, and run the tool by typing in the following command: python bundle_edges.py -c /path/to/centroids.csv -id ID_COLUMN -ew /path/to/edges.csv -o /path/to/output.gpkg If you want to adjust some parameters of the bundling, such as weights or bundling threshold use the flags -ew for edge weights (default is 2), and -t for bundling threshold (default is 2). The edge weights dictate how powerful the "gravity" of long edges are. The bundling threshold sets the distance limit for how many times longer the bundled edges can be compared to straight line distances, flows that are longer than the threshold are not bundled but remain as straight line geometries in the output. Please note, the script expects the coordinates to be in WGS84 (EPSG:4326) Test files We have provided two test CSV files that demonstrate the data structure of the required CSV files. These files can be found under the example_data directory. References Wallinger, M., Archambault, D., Auber, D., Nöllenburg, M., & Peltonen, J. (2022). Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach. IEEE Transactions on Visualization and Computer Graphics, 28(1), 313–323. https://doi.org/10.1109/TVCG.2021.3114795 Peterka, O. (2024). Xpeterk1/edge-path-bundling. https://github.com/xpeterk1/edge-path-bundling (Original work published 2023). Related links Mobi-Twin project official webpage Digital Geography Lab webpage

Zenodo

Milad Malekzadeh Mar 27

Tuomas Väisänen 📼🧟‍♂️Mar 26

🚨🌍 NEW ARTICLE 🌍🚨

We geocoded the #mobility of over 2 million #Erasmus students across #Europe from 2014 to 2022 with @miladmzdh Oula Inkeröinen & Olle Järv. The data descriptor article is published in #ScientificData, and is an output from the #MobiTwin project.

https://doi.org/10.1038/s41597-025-04789-0

@digigeolab

#GIScience #Geospatial #GIS #MobiTwin #OpenData #OpenScience

Milad Malekzadeh Mar 13

I am truly honored to share that I have been appointed to the Board of Directors of the International Professional Association for #Transport & #Health.

It is both a privilege to contribute to this incredible community at the intersection of transport and #public_health.

#SustainableMobility