Workforce-efficient consensus in crowdsourced transcription of biocollections information
We describe the challenges faced when trying to reach consensus on data transcribed by different workers. We offer consensus algorithms for textual data. We implement a consensus-based controller to assign a dynamic number of workers per task and per field of a task. We propose the use of clustering to further eliminate redundant work. We propose enhancements of future crowdsourcing task assignments in order to minimize the need for complex consensus algorithms.
crowdsourcing consensus algorithms digitization biocollections infrastructure biodiversity