Community review: a robust and scalable selection system for resource allocation within open science and innovation communities

Abstract

Resource allocation is essential to selection and implementation of innovative projects in science and technology. Current “winner-take-all” models for grant applications require significant researcher time in writing extensive project proposals, and rely on the availability of a few time-saturated volunteer experts. Such processes usually carry over several months, resulting in high effective costs compared to expected benefits. We devised an agile “community review” system to allocate micro-grants for the fast prototyping of innovative solutions. Here we describe and evaluate the implementation of this community review across 147 projects from the “Just One Giant Lab’s OpenCOVID19 initiative” and “Helpful Engineering” open research communities. The community review process uses granular review forms and requires the participation of grant applicants in the review process. Within a year, we organised 7 rounds of review, resulting in 614 reviews from 201 reviewers, and the attribution of 48 micro-grants of up to 4,000 euros. The system is fast, with a median process duration of 10 days, scalable, with a median of 4 reviewers per project independent of the total number of projects, and fair, with project rankings highly preserved after the synthetic removal of reviewers. Regarding potential bias introduced by involving applicants in the process, we find that review scores from both applicants and non-applicants have a similar correlation of r=0.28 with other reviews within a project, matching traditional approaches. Finally, we find that the ability of projects to apply to several rounds allows to foster the further implementation of successful early prototypes, as well as provide a pathway to constructively improve an initially failing proposal in an agile manner. Overall, this study quantitatively highlights the benefits of a frugal, community review system acting as a due diligence for rapid and agile resource allocation in open research and innovation programs, with implications for decentralised communities.

Education-based grant programmes for bottom-up distance learning and project catalysis: antimicrobial resistance in Sub-Saharan Africa

“…In order to ensure fairness after submission and review and prevent gamification, the reviewers’ scores across the questions in each form were normalized to their overall average review mark across their five reviews using the community review method. The distribution of scores per question shown by the heatmap indicates independence of questions asked in the form, and allowed for detection of odd reviewer behaviour [ 17 ]. ( Fig.…”

“…Similarly the funding granted for these international programmes can be more efficiently spent on capacity building rather than on flights. Prior to this study, the researchers conducted another study focusing on an agile funding allocation scheme to projects determined by applicants, and found that the correlation between reviews, with reviewers as applicants was similar to non-applicant reviewers in other schemes, and of high efficiency [ 17 ]. Following this scheme, here we used the travel spending funds towards a microgrant allocation to allow the applicants within our curriculum cohort to determine a project within their cohort that should receive seed funding for capacity building beyond education, as well as motivate their own ideas with de novo project creation.…”