Crowdsourcing Biomedial Research: Leveraging Communities as Innovation Engines

Julio Saez-Rodriguez James C. Costello Stephen H. Friend Michael R. Kellen Lara Mangravite Pablo Meyer Thea Norman Gustavo Stolovitsky

7/15/2016

Type
journal-article
Region
Sector
Health
Category
Citizen Engagement and Crowdsourcing, Data Analysis
Methodology
Conceptual Framework, Case Studies
Objective
Effectiveness

Abstract

The generation of large-scale biomedical data is creating unprecedented opportunities for basic and translational science. Typically, the data producers perform initial analyses, but it is very likely that the most informative methods may reside with other groups. Crowdsourcing the analysis of complex and massive data has emerged as a framework to find robust methodologies. When the crowdsourcing is done in the form of collaborative scientific competitions, known as Challenges, the validation of the methods is inherently addressed. Challenges also encourage open innovation, create collaborative communities to solve diverse and important biomedical problems, and foster the creation and dissemination of well-curated data repositories.