Open Science & Data Collaborations

Open Science & Data Collaborations

Open Science & Data Collaborations (OSDC) is 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.

Open Science and Data Collaboration icons

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.

You can find videos of our events on our Open Science YouTube playlist and documentation on our Open Science Framework page. For more related news, visit Open Science at CMU.


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  • Open Science Framework  – manage research data and projects, share work with collaborators, and register research with this cloud-based platform
  •  – document and share step-by-step methods and protocols
  • LabArchives  – securely record and share research notes and data in an Electronic Research Notebook
  • KiltHub Repository  – make all of the products of your research openly available and citable with CMU’s institutional repository



  • Carpentries Workshops – 2-day introductions to coding with R, Python, shell, and Git
  • Libraries Workshops – short workshops on getting started with research tools from Zotero to Jupyter Notebooks and research practices from literature searching to data management
  • OSDC MiniSeries: Reproducible Research – 2 to 3-hour workshops that focus on basic concepts, skills, and tools for conducting research in a reproducible manner. You can find recordings of some of these workshops on CMU Libraries YouTube Tutorials & Workshops playlist.



  • Open Science Symposium - A semi-annual symposium that brings together researchers, funders, publishers, and tool developers to discuss the challenges and opportunities of open research.
  • AIDR: Artificial Intelligence for Data Discovery and Reuse - A semi-annual symposium focused on harnessing the power of AI to accelerate the dissemination and reuse of scientific data and building a healthy data ecosystem.



  • Data Collaborations Lab (dataCoLAB) - We match up researchers who want help with their datasets with consultants who have data science skills, and create opportunities for people with different technical and disciplinary backgrounds to work together, following best practices that enhance reproducibility.
  • Collaborative Bioinformatics Hackathon - Academic and industry researchers from around the world come together to collaboratively work on crucial problems and opportunities in clinical bioinformatics.



  • Consultations: Book an in-person or virtual consultation for help with a large variety of topics related to open and reproducible research including coding in R or Python, data cleaning, and sharing data.
  • 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.


The Open Science Team

  • Katie Behrman, KiltHub Repository Coordinator

  • Lencia Beltran, Open Science Program Coordinator

  • Emily Bongiovanni, Psychology

  • Melanie Gainey, Program Director

  • Chasz Griego, Open Science PostDoctoral Associate

  • Emma Slayton, Data Curation, Visualization, & GIS Consultant

  • Sarah Young, Social Sciences, Public Policy and Information Systems; Evidence Synthesis



Advisory Board

  • Christina Akirtava, Graduate Student, Biological Sciences, CMU
  • John Chin, Research Coordinator, Institute for Politics & Strategy, CMU
  • Jeffrey Flagg, Lab Manager, Dynamic Decision Making Laboratory, CMU
  • Nynke Niezink, Assistant Professor, Department of Statistics and Data Science, CMU
  • Albert Presto, Research Professor, Mechanical Engineering, CMU
  • Scott Renshaw, Postdoctoral Research Associate, at the Center for Informed Democracy & Social-Cybersecurity (IDeaS), CMU
  • Thiago Rodrigues, Doctoral Student, Civil & Environmental Engineering, CMU
  • Cathy Su, Doctoral Student, Computational Biology, CMU



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