Capturing the Forest or the Trees: Designing for Granularity in Data Crowdsourcing Murphy, Ryan Parsons, Jeff 2020-01-04T07:12:59Z 2020-01-04T07:12:59Z 2020-01-07
dc.description.abstract Crowdsourcing is a method of completing a task by engaging a large group of heterogeneous contributors. Data crowdsourcing is crowdsourcing of data collection. In this paper, we demonstrate how data crowdsourcing projects can be differentiated along five dimensions: (1) the extent to which tasks are well-defined; (2) the duration of the task; (3) the type of value generated by the consumers of crowdsourcing data; (4) the variety of contribution allowed when completing the task; and (5) the relative value of each contribution. We argue that the quality of information created by a crowd depends on the granularity of contributions contributors are able to make. Finally, we propose a set of principles for designing crowdsourcing system to align the level of granularity of contributions with project objectives.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2020.049
dc.identifier.isbn 978-0-9981331-3-3
dc.language.iso eng
dc.relation.ispartof Proceedings of the 53rd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Design and Development of Collaboration Technologies
dc.subject conceptual modeling
dc.subject crowdsourcing
dc.subject data
dc.subject granularity
dc.title Capturing the Forest or the Trees: Designing for Granularity in Data Crowdsourcing
dc.type Conference Paper
dc.type.dcmi Text
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