Reaching Consensus in Crowdsourced Transcription of Biocollections Information

TitleReaching Consensus in Crowdsourced Transcription of Biocollections Information
Publication TypeConference Paper
Year of Publication2014
AuthorsMatsunaga, Andréa, Mast Austin, and Fortes José A. B.
Conference Name2014 IEEE 10th International Conference on e-Science
Date PublishedOct/2014
Conference LocationGuarujá, Brazil
Other Numbers6972249
KeywordsAccuracy, Approximation algorithms, biocollections infrastructure, biodiversity, consensus algorithms, crowdsourcing, digitization, EF-1115210, Heuristic algorithms, Materials, Optical character recognition software, Reliability
AbstractCrowdsourcing can be a cost-effective method for tackling the problem of digitizing historical bio collections data, and a number of crowd sourcing platforms have been developed to facilitate interaction with the public and to design simple "Human Intelligence Tasks". However, the problem of reaching consensus on the response of the crowd is still challenging for tasks for which a simple majority vote is inadequate. This paper (a) describes the challenges faced when trying to reach consensus on data transcribed by different workers, (b) offers consensus algorithms for textual data and a consensus-based controller to assign a dynamic number of workers per task, and (c) proposes further enhancements of future crowd sourcing tasks in order to minimize the need for complex consensus algorithms. Experiments using the proposed algorithms show up to a 45-fold increase in ability to reach consensus when compared to majority voting using exact string matching. In addition, the controller is able to decrease the crowd sourcing cost by 55% when compared to a strategy that uses a fixed number of workers.