OpenProposal Platform for Transparent Research Funding Review
Sakshi Ahuja, Subhankar Mishra
TL;DR
The paper addresses the opacity of research funding review and its impact on feedback and learning. It proposes OpenProposal, a proof-of-concept platform inspired by OpenReview that enables public reviews, author rebuttals, and community engagement while protecting sensitive information like budgets. A three-tier technical architecture (Next.js/React frontend, Prisma ORM, PostgreSQL) and a transparent workflow from submission to publication are described, demonstrating feasibility and design considerations. The work discusses potential benefits such as improved review quality and reduced bias, while acknowledging limitations and the need for empirical validation through pilot studies and policy alignment.
Abstract
Research funding allocation remains a critical bottleneck in scientific advancement, yet the review process for funding proposals lacks the transparency that has revolutionized academic paper peer review. Traditional funding agencies operate with closed review systems, limiting accountability and preventing systematic improvements. We present OpenProposal, a proof-of-concept web-based platform that explores how transparency principles from OpenReview might be adapted to research funding proposal evaluation. Built using modern web technologies including Next.js , React , and Prisma , OpenProposal demonstrates the technical feasibility of public reviews, author rebuttals, and transparent decision-making while attempting to protect sensitive information such as budgets. Our platform prototype addresses key limitations identified in current funding systems by providing mechanisms for community engagement, reviewer accountability, and potential data-driven insights into peer review processes. Through system design and implementation, we explore how transparent funding review could potentially enhance scientific integrity and improve research funding decisions, though empirical validation remains necessary. This work contributes a technical foundation for transparent funding review and identifies design considerations for future research on peer review mechanisms in funding contexts.
