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CROWD-BASED DATA-DRIVEN HYPOTHESIS GENERATION FROM DATA AND THE ORGANISATION OF PARTICIPATIVE SCIENTIFIC PROCESS

Abstract : In scientific process, hypothesis generation is one the most important steps where creativity is needed most. As the science becomes more open and data-driven, it becomes interesting to analyse whether a crowdsourcing approach might be beneficial in this step. First, we characterize the process as a design process. Then, based on a real-life case study, we analyse and highlight difficulties and challenges for crowd-based hypothesis generation. Last, we give a generic process model for organizing in similar challenges in other data-based scientific hypothesis generation contexts.
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https://hal.archives-ouvertes.fr/hal-01787696
Contributor : Yohann Sitruk <>
Submitted on : Monday, May 7, 2018 - 5:14:53 PM
Last modification on : Thursday, April 9, 2020 - 5:08:14 PM
Document(s) archivé(s) le : Monday, September 24, 2018 - 12:32:48 PM

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  • HAL Id : hal-01787696, version 1

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Yohann Sitruk, Akin Kazakçi. CROWD-BASED DATA-DRIVEN HYPOTHESIS GENERATION FROM DATA AND THE ORGANISATION OF PARTICIPATIVE SCIENTIFIC PROCESS. Design 2018 Conference, May 2018, Dubrovnik, Croatia. ⟨hal-01787696⟩

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