Open Science & Data Collaborations
A University Libraries program supporting collaborative, transparent, openly accessible, and reproducible research across all disciplines at Carnegie Mellon University. We recognize that having well documented and automated research workflows, code, and datasets is essential to making research more interdisciplinary, efficient, and reusable as well as allowing researchers to leverage data science techniques. This program provides services and infrastructure for open research at CMU through digital tools, training opportunities for research tools and practices, collaboration opportunities on data science projects, special events and advocacy, and a team of experts available as research consultants and collaborators.
The Open Science Team
Katie Behrman, KiltHub Repository Coordinator
Melanie Gainey, Biological Sciences, Biomedical Engineering
Hannah Gunderman, Research Data Consultant; Data Management
Huajin Wang, Biological Sciences, Computer Science, Data Collaborations and Reproducibility
Sarah Young, Social Sciences, Public Policy and Information Systems; Evidence Synthesis
• Open Science Framework – Data management and registration for collaborative research projects
• Protocols.io – the recipe book for your research
• KiltHub Repository – make all of the products of your research openly available, citable, and reusable
• LabArchives – Electronic Research Notebook to securely record and share research notes
• Carpentries Workshops – 2-day introductions to scientific computing with R and Python
• Libraries Workshops – local workshops on getting started with research tools from Mendeley to Jupyter and research practices from literature searching to data management
• Hackathons and workshops on reproducible science - find events on the Libraries calendar
Data Collaborations Lab (dataCoLAB) — We match up researchers who want help with their datasets with consultants who have data and computer science skills, and create opportunities for people with different technical and disciplinary backgrounds to work together, following best practices that enhance reproducibility.
• Open Science Symposium: Each fall we host a symposium bringing together researchers, funders, publishers, and tool developers to discuss the challenges and opportunities of open research. Program and video of talks available online for OSS2018 (video: https://osf.io/54gue/) and OSS 2019 (video: https://osf.io/f6gkw/)
• AIDR: Artificial Intelligence for Data Discovery and Reuse: First hosted in 2019 as an NSF-funded conference aiming to find innovative solutions to accelerate the dissemination and reuse of scientific data in the data science revolution. In 2020, a 1-day symposium version will be held on May 11, 2020 (postponed due to COVID-19).
• Love Data Week – an international celebration of data each February.
• Consultations - Get in touch for help with any stage of the research process from grant writing and data management plans, to reproducible analysis workflows, to making any or all products of your research open.
• Collaborations – We’re researchers too and would be glad to be partners on your research projects to contribute to data management or open data components of the work.
• Outreach – We’ll come to you! Get in touch if you’d like us to pay a visit to your lab, program, department, or other CMU community group.