FAIR Data Fund Spring Call 2021: Meet the grantees

Claudiu Forgaci 

Assis­tant Pro­fes­sor in Urban Design at Delft Uni­ver­si­ty of Tech­nol­o­gy  @claudiuforgaci

Claudiu is engaged in under­stand­ing how spa­tial urban­i­sa­tion pat­terns, at mul­ti­ple spa­tial and tem­po­ral scales, are relat­ed to social-eco­log­i­cal resilience in cities. 

With the help of the FAIR Data Fund, Claudiu aims to make the qual­i­ta­tive and quan­ti­ta­tive find­ings of the I‑SURF project, as well as its urban design-dri­ven research method­ol­o­gy, avail­able to the wider com­mu­ni­ty of researchers and prac­ti­tion­ers. The data man­age­ment pipeline will be doc­u­ment­ed in detail to make sure that the data, work­flows and code are FAIR.

Frank Halfwerk

Assis­tant Pro­fes­sor in Bio­me­chan­i­cal Engi­neer­ing at the Uni­ver­si­ty of Twente

Frank is a Tech­ni­cal Physi­cian in car­dio-tho­racic surgery and the Direc­tor of the Car­diac Surgery Inno­va­tions Lab. He applied for the FAIR Data Fund with the aim of mak­ing this his full sci­en­tif­ic career FAIR. Using the fund, he will make all of his data under­ly­ing peer-reviewed pub­li­ca­tions avail­able accord­ing to the FAIR prin­ci­ples.

Michelle Kip & Ria Wolkorte 

Post­doc­tor­al researchers in Health Tech­nol­o­gy & Ser­vices Research at the Uni­ver­si­ty of Twente
@Michelle_Kip, @UTwenteHTSR

Michelle and Ria work in the field of (ear­ly) Health Tech­nol­o­gy Assess­ment. Their research focus­es on eval­u­at­ing the impacts of health­care tech­nol­o­gy in terms of health out­comes, well-being and costs. Through apply­ing cit­i­zen sci­ence method­ol­o­gy, they aim to increase the role of cit­i­zens in the process of health­care tech­nol­o­gy devel­op­ment and imple­men­ta­tion.

Their dataset con­cerns rheuma­toid arthri­tis patients’ opin­ions on research top­ics, dig­i­tal envi­ron­ments for cit­i­zen sci­ence and their desired roles in sci­en­tif­ic research. Increas­ing the lev­el of FAIR for this dataset, and future data col­lec­tion and pub­li­ca­tion by TOPFIT Cit­i­zen­lab is in line with the prin­ci­ples of cit­i­zen sci­ence.

João Moreira 

Assis­tant Pro­fes­sor in Ser­vices and Cyber Secu­ri­ty at the Uni­ver­si­ty of Twente

João has a back­ground in com­put­er sci­ence, par­tic­u­lar­ly soft­ware engi­neer­ing, and his research tar­gets seman­tic inter­op­er­abil­i­ty of ICT solu­tions for seam­less data inte­gra­tion and ana­lyt­ics.

João’s datasets to be refined and pub­lished in the 4TU.ResearchData data repos­i­to­ry are gen­er­at­ed by the Sys­tems Life Cycle Lab­o­ra­to­ry (SysLCM-Lab). The SysLCM-Lab offers indus­tri­al engi­neer­ing and com­put­er sci­ence stu­dents an oppor­tu­ni­ty to remote­ly per­form exper­i­ments relat­ed to the Smart Indus­try, Indus­try 4.0 and Dig­i­tal Twins dur­ing assign­ments. The cur­rent assign­ment enables stu­dents to assem­ble a ‘hov­er in a box’.

Thomas Groen

Asso­ciate Pro­fes­sor in Nat­ur­al Resources at the Uni­ver­si­ty of Twente
@ta_groen

Thomas stud­ies bio­di­ver­si­ty, con­ser­va­tion and remote sens­ing. With the aim of inform­ing soci­ety about the fate of semi-nat­ur­al ecosys­tems, Thomas uses empir­i­cal spa­tial inter­po­la­tion tech­niques and ther­mal infrared remote sens­ing tech­niques to extract ear­ly warn­ing sig­nals of tip­ping points in ecosys­tems from satel­lite time series.

Using the FAIR Data Fund and the help of stu­dent assis­tant, Nivedi­ta Var­ma Harise­na, Thomas will refine data and code under­ly­ing his pub­li­ca­tion, ‘When is vari­able impor­tance esti­ma­tion in species dis­tri­b­u­tion mod­el­ling affect­ed by spa­tial cor­re­la­tion?’

Their aim is to cre­ate a guide­book that allows future users of Species Dis­tri­b­u­tion Mod­els to be able to change mod­el para­me­ters, visu­alise the results and reuse the mod­els with­in their own con­text.

Pavlo Bazilinskyy

Post­doc­tor­al researcher in Cog­ni­tive Robot­ics at Delft Uni­ver­si­ty of Tech­nol­o­gy
@bazilinskyy

Pavlo is the Head of Data Research at SD-Insights and a researcher study­ing the human fac­tors of auto­mat­ed dri­ving. 

He believes that auto­mat­ed dri­ving will save mil­lions of lives. His refined dataset will pro­vide researchers with a bet­ter under­stand­ing of the inter­ac­tions between auto­mat­ed vehi­cles and mul­ti­ple road users. It con­tains data from a cou­pled sim­u­la­tor capa­ble of run­ning immer­sive sim­u­la­tions with dozens of peo­ple, and record­ing of a real traf­fic sit­u­a­tion from a portable sen­sor.

The FAIR Data Fund offers researchers a bud­get (up to €3.500) to cov­er the costs of mak­ing their data Find­able, Acces­si­ble, Inter­op­er­a­ble and Reusable (FAIR data prin­ci­ples). Researchers from TU Delft, TU/Eindhoven and the Uni­ver­si­ty of Twente are eli­gi­ble to apply for the fund. 

Appli­ca­tions for the FAIR Data Fund Spring Call are now closed. Sub­scribe to our newslet­ter to stay updat­ed about the Autumn Call.