The C-Score: Incentivizing Collaboration

A Reward System to Promote Team Science and the Overall Progress of the Scientific Enterprise

Given the increasing connectivity between fields and specialties of science, there is an increasing need for collaboration, yet a system of winner-takes-all is inherently unfair to collaborators. A different reward system could promote team science and thus promote the overall progress of the scientific enterprise.[1]

— Arturo Casadevall, Editor in Chief, mBio and Ferric C. Fang, Editor in Chief, Infection & Immunity

A Crippling Problem

The primary reputation currency in the sciences, and the chief determinant of whether a researcher is hired, promoted and funded, is the published paper and the journal in which it appears. Thomson Reuters’ Impact Factor (IF), which reflects citation rates of a journal’s articles, is a key reputation metric, even though it’s been challenged as an indicator of research quality.  An author’s H-index is similarly based on article citations but without regard to journal status. Altmetrics have developed to measure the impact of papers in social media outlets such as Twitter, blogs, and social bookmarking systems. [2]

However, despite emerging revisionist reward systems, the traditional published paper remains the ballast of scientists’ careers. Moreover, researchers’ fears of being scooped by competitors constrain them from sharing important insights in collaborative projects in which a systems approach is required to find solutions. Dr. Ewan Birney, project lead on the massive NIH-funded “Encyclopedia of DNA Elements,” noted in his editorial The Making of ENCODE: Lessons for Big-Data Projects (Nature, Sep 5, 2012) that in consortium science, “researchers must focus on creating the best data set they can. Maybe they will use the data, maybe they won’t. What is important is the community resource, not individual success… In turn, the success of participants must be measured at least as much by how their data have enabled science as by the insights they have produced.”

A Common-Sense Solution

In science, as in so many parts of life, what gets measured is what gets rewarded, and what gets rewarded is what gets done. — M. Nielsen [3]

Today’s research often requires massive datasets and specialized expertise for discovery and problem-solving. A remarkable number of grants are now being awarded that require collaborative effort, as exemplified by the National Institute of Medical Sciences 2017 announcement of “a new program to support collaborative, team-based science… as a result of evaluations of our previous programs, recent research on the science of team science, and community input.” We believe that these efforts will fail in the absence of an alternative to publishing as the sole reward system for research contributions.

The Collaboration Score, or C-Score, will reward participants’ contributions to a project, as well as their rapid, open dissemination of findings (see design pages with descriptions, exemplary credits for scoring algorithm, and an interactive demo of participant and funder/admin views on the project platform). The algorithm being devised will measure an array of activities, which will also be viewable by funders and administrators in participants’ profiles on the project platform, diminishing the possibilities for gaming of scores. Some of those activities include:

  • sharing research findings, patient data, and other information – high scores for early and wide dissemination
  • generating hypotheses that are incorporated in the group’s communications
  • moderating/initiating/participating in discussions
  • posting/rating/commenting on the latest published literature and clinical trials
  • rating/reviewing co-investigators’ findings
  • contributing statistical analyses, data curation, software development and new methodologies
  • demonstrating reproducibility
  • leading/participating in cross-group committees–e.g, protocols, data standardization
  • Iterating/updating one’s findings or case reports based on feedback or new evidence
  • coauthoring/peer-reviewing content to be disseminated – including the team’s Evidence Review
  • publishing incremental and null results, editorials, reviews

Development of the metric and rankings is being led by reputation experts, drawing from the insights and expertise of mathematicians, computer scientists, economists, and behavioral scientists, as well as researchers themselves and funding officials, academic administrators, and other parties.

See “The Singular Barrier to Collaboration (and why Sean Parker is worried)“.

See Further Reading for references on this and related topics.

See the Design Prototype (a work in progress).

If you would like to participate in formulating the C-Score, please contact us: edit at rapidscience dot org.

Example C-Score

See the Design Prototype  (a work in progress).


Frederick M. Ausubel, PhD, Professor of Genetics, Harvard Medical School and the Karl Winnacker Distinguished Investigator in the Department of Molecular Biology at Massachusetts General Hospital; founding editor of Current Protocols in Molecular Biology; well known for pioneering contributions to the genetic analysis of host-microbe interactions.

Philip E. Bourne, PhD, founding Editor-in-Chief of PLOS Computational Biology and Director of the Data Science Institute at University of Virginia; previously he was Director for Data Science at NIH where he managed the Big Data to Knowledge initiative and Associate Vice Chancellor for Innovation and Industry Alliances at UCSD.

James G. Boyle, PhD, Managing Director of the Yale Entrepreneurial Institute; as co-founder of YEI in late 2006, has forged partnerships and funding opportunities for Yale University innovators.

Amy Brand, PhD, Director of MIT Press; leading proponent of open science and co-chair of Project CRediT (Contributor Roles Taxonomy), an initiative led by The Wellcome Trust and Digital Science to develop recommendations for a new taxonomy of research contribution.

Arturo Casadevall, MD, PhD, Chair and Bloomberg Distinguished Professor of Molecular Biology and Immunology, School of Medicine, Johns Hopkins University; well known for his publications and analyses of the funding pipeline in scientific research, biases and retractions in journal publishing, and the complex ethics of dual use research.

Melissa Haendel, PhD, Co-Director of the OHSU Library and an Associate Professor in the Library and the Department of Medical Informatics and Clinical Epidemiology; interests include open science, promotion of research reproducibility, and development of ontologies and data standards.

Kristi Holmes, PhD, Director of the Galter Health Sciences Library and Associate Professor, Preventative Medicine-Health and Biomedical Informatics at the Feinberg School of Medicine, Northwestern University; the Northwestern University Clinical and Translational Sciences Institute; interests include open science and understanding the impact of research efforts.

Julia Lane, PhD, economist and Professor at NYU’s Center for Urban Science & Progress at the Wagner Graduate School of Public Service; Provostial Fellow for Innovation Analytics and Senior Fellow at NYU’s GovLab; co-founder of the UMETRICS and STAR METRICS programs at NSF among many other initiatives and institutions.

Jessica Polka, PhD, Executive Director of ASAPbio, a non-profit promoting transparency and innovation in scholarly communication at the Department of Cellular and Molecular Pharmacology, UCSF;  Visiting Scholar at the Whitehead Institute and Visiting Postdoctoral Research Fellow in the Department of Systems Biology, Harvard Medical School.

Kristen Ratan, MSc, publishing executive and well-known strategist and implementer of open science initiatives; co-founder and Executive Director of  Collaborative Knowledge Foundation, building open source solutions in scholarly knowledge production that foster collaboration, integrity, and speed.

Griffin Weber, MD, PhD, Associate Professor of Medicine in the Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, and Harvard Medical School, and the Director of the Biomedical Research Informatics Core (BRIC) at Beth Israel Deaconess Medical Center; research includes expertise mining and social network analysis; inventor of Profiles RNS, an open source social networking website for scientists.

Zehn Zhang, PhD, Director of Bioinformatics and Biostatistics, Center for Biomarker Discovery and Translation, and Associate Professor of Pathology and Oncology at Johns Hopkins Medical Institute; research focuses on developing bioinformatics tools applicable to clinical diagnoses; co-developed the first FDA-cleared in vitro diagnostic multivariate index assay, the OVA1 test for ovarian cancer.