000163965 001__ 163965
000163965 005__ 20251113160752.0
000163965 0247_ $$2doi$$a10.1145/3733600
000163965 0248_ $$2sideral$$a146062
000163965 037__ $$aART-2025-146062
000163965 041__ $$aeng
000163965 100__ $$aHerrera-Murillo, Dagoberto José$$uUniversidad de Zaragoza
000163965 245__ $$aCollective Intelligence in Humanitarian Voluntary Geographic Information: The Case of the HOT Tasking Manager
000163965 260__ $$c2025
000163965 5060_ $$aAccess copy available to the general public$$fUnrestricted
000163965 5203_ $$aVoluntary Geographic Information initiatives are transforming the disaster response landscape. Our research provides insights into how the concept of collective intelligence is accomplished in humanitarian mapping initiatives. The main source originates from the data obtained in 746 mapping projects organised by the Humanitarian OpenStreetMap Team between December 2021 and November 2023, where 38,893 contributors completed 312,289 mapping tasks. These data include detailed attributes of the contributors and the states the tasks go through. The methodology adopts a quantitative approach, including descriptive and inferential statistics, and standard process mining techniques. Our results indicate that, in general terms, in humanitarian mapping, a group of contributors from outside the area of interest perform straightforward mapping tasks with limited collaboration among them. The ‘wisdom’ of advanced contributors is the cornerstone that sustains the system. The discussion section elaborates on (1) how these findings suggest that humanitarian mapping projects effectively meet their short-term mapping objectives but fall short if more sustainable mapping objectives are sought and (2) possible strategies for better harnessing the collective intelligence of these efforts.
000163965 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T59-23R$$9info:eu-repo/grantAgreement/EC/H2020/955569/EU/Towards a sustainable Open Data ECOsystem/ODECO$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 955569-ODECO
000163965 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000163965 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000163965 700__ $$aOchoa-Ortiz, Héctor
000163965 700__ $$aAhmed, Umair
000163965 700__ $$0(orcid)0000-0001-6491-7430$$aLopez-Pellicer, Francisco J.$$uUniversidad de Zaragoza
000163965 700__ $$aRe, Barbara
000163965 700__ $$aPolini, Andrea
000163965 700__ $$0(orcid)0000-0002-1279-0367$$aNogueras-Iso, Javier$$uUniversidad de Zaragoza
000163965 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000163965 773__ $$g32, 5 (2025), 1-38$$pACM Transactions on Computer-Human Interaction$$tACM Transactions on Computer-Human Interaction$$x1073-0516
000163965 8564_ $$s5853461$$uhttps://zaguan.unizar.es/record/163965/files/texto_completo.pdf$$yPostprint
000163965 8564_ $$s2035664$$uhttps://zaguan.unizar.es/record/163965/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000163965 909CO $$ooai:zaguan.unizar.es:163965$$particulos$$pdriver
000163965 951__ $$a2025-11-13-14:58:42
000163965 980__ $$aARTICLE