CS&S is proud to announce that OpenReview has joined our Sponsored Project Program.

OpenReview has been working since 2013 on peer review workflow systems that enable publication venues to explore varying types of openness.  They have already supported significant innovations in open peer review by ICLR, UAI, and many other computer science conferences and workshops. We are thrilled that they are joining our community! With a recent influx of funding from the Chan Zuckerberg Initiative, OpenReview is poised to grow. Read on for more from OpenReview's Andrew McCallum.

Front left to right: Michael Spector, Pam Mandler. Middle row left to right: Mohit Uniyal, Melisa Bok, Andrew McCallum. Back row: David Marshall.

Peer review is ripe for a revolution.  Current scientific peer review workflows were designed in the days of on-paper publishing and postal courier service.  The scientific community is increasingly questioning the efficacy and fairness of current peer review practices. Individual research communities are expressing frustration with existing systems, as well as willingness to try new reviewing workflows. Even in communities satisfied with their existing reviewing workflow, there are complaints about the data/software infrastructure that limits efficiency.  Our vision is to provide a highly configurable, scalable, and open online peer review workflow that allow different scientific communities to deliberately explore revolutions in “who gets to see what when” during peer review.  We are also deploying the latest modern machine learning and natural language processing research to provide better review-paper matching systems, models of scientific expertise, knowledge bases of scientific concepts, understanding of the dynamics of scientific sub-communities, and a massive knowledge base of scientists’ career paths and their conflicts of interest.

We are proud to announce that OpenReview has received grant of $1.8 million over three years from the Chan Zuckerberg Initiative. The focus of this grant is to expand support for knowledge bases of science, with work in machine learning, development of next generation ontologies, natural language processing, and more in collaboration with CZI's Meta project. Prototypes and other components will be released as open source code, through open GitHub repositories, under the Apache 2.0 license.