The Open Science & Data Collaborations Program strives to empower our community with knowledge about open science practices, tools, and resources, enabling individuals to embrace one or more open practices. This, in turn, enhances the accessibility, reproducibility, and discovery of scholarly activities across diverse fields.
1. Transparency
2. Reproducibility
3. Inclusion and Diversity
4. Collaboration
Tools: We furnish licenses and comprehensive training for a range of digital research tools. These resources support research reproducibility, collaboration, and data sharing. Some notable tools include the Open Science Framework, protocols.io, LabArchives, and our institutional repository, KiltHub.
Training: Our commitment extends to providing workshops and various forms of training to equip researchers with essential data literacy skills. These skills are fundamental for conducting transparent and reproducible research.
Events: We actively organize conferences, hackathons, and other engaging events. These gatherings not only raise awareness but also serve as platforms to unite and galvanize the open research community, both within CMU and in broader academic spheres.
Collaboration: Leveraging our extensive partnerships across campus, we create opportunities for interdisciplinary collaboration. By fostering a healthy data ecosystem that promotes data reuse, we contribute to the growth of a healthy research environment.
Research and Assessment: Our team engages in research on topics about open science like reproducible research, systematic reviews, open science training, and so on. Additionally, we conduct assessments to continually evaluate the adoption and impact of open science practices, not only at CMU but also on a broader scale.
As a collective of subject experts and information specialists with diverse disciplinary knowledge, we are uniquely positioned to tailor our support to researchers across various fields and disciplines.
The Carnegie Mellon University Libraries Open Science Program, also known as Open Science and Data Collaborations (OSDC), was founded in 2018. The program team members are a combination of Library liaisons and functional specialists, an open science director, and an open science coordinator. The program also has an Open Science Advisory Board whose members are from across the institution.
View upcoming and past workshops on our Open Data Science GitHub page!
Book an in person or virtual consultation for help with R, Python, or other data needs. We have a team of experts on hand to help you!
This work is licensed under CC BY 4.0
