Winners of the 5th edition of the FAIR Data Fund

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.

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.

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.

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

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.

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.

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.

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.