Winners of the 5th edition of the FAIR Data Fund
We are happy to announce the winners of the 5th edition of the FAIR Data Fund. In total, we’ve selected 8 grantees representing our partner universities and a variety of scientific disciplines. Please see them listed below.
Congratulations to all and we look forward to supporting your work this year!
Elad Horn – Delft University of Technology
Architectural history
This dataset contains about 40 high-resolution historical maps and plans of Jaffa–Tel Aviv (1800–present) in TIFF/JPEG/PDF formats. Documentation is partial, with basic file naming and a preliminary spreadsheet listing sources, dates, titles, and limited scale/author details.
Milad Naderloo – Delft University of Technology
Geomechanics and Multiphase Flow in Subsurface Energy Storage
This dataset holds CT scans of geological materials with raw projections, 3D reconstructions, and instrument metadata in mixed formats. The project standardizes files into structured folders with JSON-LD metadata and READMEs, producing FAIR, AI-ready data and a reusable FAIRification workflow.
Dian Zheng – Wageningen University & Research
Phytopathology
This dataset includes raw long-read and Illumina sequencing reads, assembled genomes, variant files, and summary tables. Metadata follows MIxS standards in JSON/CSV, with QC reports and reproducible workflow scripts hosted on GitHub.
Ignacio Saldivia Gonzatti – Wageningen University & Research
Agro-climatology
Bias-corrected and statistically downscaled seasonal climate hindcasts for Ghana, Kenya, and Zimbabwe are combined with LPJmL-generated crop yield hindcasts. Data include precipitation, temperature, radiation, and wind speed ensembles at multiple lead times, stored as NetCDF model outputs organized by variable, lead time, and country. Supporting bash and Python scripts are version-controlled but mainly internally documented with limited user metadata
Emil Georgiev – Wageningen University & Research
Sustainable Value Chains
This project uses farm-level sustainability data (yields, fertilizer use, energy, water), Life Cycle Inventory (LCI) datasets for agricultural inputs, and supplier-reported KPIs from THESIS. It also includes modeled environmental impacts (GHG, water, land use) and metadata for provenance and quality.
Mohammad Shadab Alam – Eindhoven University of Technology
Data Science, Traffic Study
TraffCOCO is a developing traffic dataset built on an existing 4TU.ResearchData deposit from the “Pedestrian Planet” project, which analyzed global dashcam footage from the CROWD dataset to produce processed research outputs and supporting materials.
Pavlo Bazilinskyy – Eindhoven University of Technology
Human Factors
This research collection totals ~18 TB, mainly dashcam videos, computer-vision derivatives, and models/logs. The curated FAIR subset for 4TU.ResearchData will include annotations, trajectories, segmentation outputs, configs, and metadata, estimated at ~2.1 TB, with extra storage requested if needed.
Bob Sammy Munyoki Mwende – University of Twente
Forest Agriculture and Environment in the Spatial Sciences (FORAGES)
This research enhances drought monitoring in Kenya’s ASALs by testing LoRaWAN environmental sensors and crowd-sourced imagery, then integrating these in-situ data with satellite observations.
For more information on the FAIR Data Fund, please have a look at the dedicated webpage or send us an email at fairdatafund@4tu.nl.
