Titre : Data correction for transcription in crowdsourcing. A feedback from RECITAL platform. Auteurs : Benjamin HERVY, Pierre PÉTILLON, Hugo PIGEON, Guillaume RASCHIA, Revue : Information Retrieval, Document and Semantic Web Numéro : Issue 1 Volume : 2 Date : 2019/03/18 DOI : 10.21494/ISTE.OP.2019.0348 ISSN : 2516-3280 Résumé : Crowdsourcing have been widely deployed to cover some challenges in digital humanities, like in the transcription of old handwritten documents. Such approach is especially useful to tackle existing limits in automatic handwriting recognition techniques. Crowdsourcing allows workers to help experts in extraction and classification of information, when the workload is daunting. Yet, it yields some specific challenges related to the quality of produced data. In this paper, we discuss data quality in a research project called CIRESFI which aims at transcribing Italian Comedy financial archives through the RECITAL web platform.We finally propose some leads to tackle these issues. Éditeur : ISTE OpenScience