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Session Recording

Holistic Approaches to Open Science and Publishing Infrastructures: Case Studies from Carnegie Mellon University and F1000 Recording

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While US-based scholars tend to be under fewer mandates to publish openly compared to their European-based colleagues, an increasing amount of policies, practices, and guidelines are helping to encourage openness from data to code to publication. With this in mind, openness-supporting approaches for only more traditional formats of research output are not comprehensive enough. Libraries are responding by creating greater infrastructure to support scholars, and publishers are responding by reassessing models and reviewing ways to scaffold greater transparency. In this session, we will present two ways researchers are being supported in their open pathway: one from a library, and one from a platform perspective. The Open Science & Data Collaborations (OSDC) program at Carnegie Mellon University (CMU) supports collaborative, transparent, openly accessible, and reproducible research across all disciplines. This program, which centers librarians as expert consultants and collaborators, provides services and infrastructure for open research through advocacy, digital tools, training opportunities on research tools and practices, collaboration opportunities for data science projects, and special events. F1000 (part of the Taylor & Francis group) launched almost ten years ago to address the calls for better solutions to the reproducibility and replicability crises. The F1000 publishing model places openness at its center by requiring FAIR compliant data with submission, allowing for a broad variety of publication types beyond standard journal articles, and using open community peer review to validate research. The model is in use at the Gates Foundation, the Wellcome Trust, institutions, and at a discipline level through subject gateways and platforms. Both CMU and F1000 will join to discuss the impact of these approaches on researchers that use their respective program and platform. Session attendees will learn about the ways that rethinking infrastructure and models can ensure more open science and a greater impact for faculty.