Open Science at CMU Newsletter - July 2019



We are wrapping up our first year of the University Libraries Open Science Program, which has included the inaugural Open Science Symposium, four Software and Data Carpentry workshops, the inaugural AIDR (Artificial Intelligence for Data Discovery and Reuse Conference), stand-alone workshops on topics such as Open Refine, Open Science Framework, and Reproducible Research, and new institutional licenses for and Open Science Framework.  We are looking forward to another year of exciting programming, and this newsletter will keep you informed of our upcoming events, new digital tools, and training opportunities.  

You can contact us at and follow us at #CMUOpenScience. 

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Registration Open for Python Data Carpentry Workshop, July 22 & 23

Join us for a 2-day hands-on introductory workshop for using Python, OpenRefine, and SQL for working with data from The Carpentries. This workshop is suitable for those with little to no programming experience.  Light breakfast and lunch will be provided. You can find more info on the workshop website and register here

We will also host an R Software Carpentry Workshop on August 21 & 22 and are planning more Python workshops for the fall semester. Check the Libraries events calendar for these to come. 

Students, staff, postdocs, and faculty learning data skills in R at our Data Carpentry Workshop on June 4-5, 2019

Save the Date for the Second Open Science Symposium on November 7, 2019 

Join us for a day focused on the opportunities and challenges of practicing open science. The full day program will feature talks from guest speakers including researchers, tool developers, funders, and publishers; a poster session on research using open methods; and a collaboration networking reception. 

Watch the Open Science Symposium 2019 website for program updates. Registration and a call for posters will be coming later this summer. You can also check out last year's Open Science Symposium.  
Take Advantage of our New Institutional License for 

The platform is a free and open access repository for recording and sharing detailed up-to-date research methods and protocols. It allows researchers to easily create, edit, share, and get credit for their protocols, and provides an open access hub for scientists to communicate improvements and corrections to scientific methods. The platform is useful for any discipline that uses a step-by-step methodology, such as biology, chemistry, neuroscience, engineering, data science, and other computational or life science fields. 

CMU students, staff, and researchers can learn how to make the most of our institutional license by viewing this brief webinar or checking out our website

Meet the CMU Libraries Open Science Program Team  
Ana Van Gulick, Open Science Program Director and Research Liaison to Psychology and Brain Sciences

I first joined the University Libraries in 2014 as a postdoctoral fellow for data curation after completing a PhD in Cognitive Psychology at Vanderbilt. For the past 3 years I've served as the liaison librarian to psychology and neuroscience and have focused on data sharing, open science, and transparent and reproducible research workflows. In September 2018, I took on the role of Program Director for Open Science in the Libraries to coordinate our open science support through trainings, outreach, digital infrastructure, and expert collaborators both within the Libraries and across CMU.  
Melanie Gainey, Library Liaison to Biological Sciences & Biomedical Engineering 

I joined University Libraries in 2017 after completing a postdoc in neuroscience at U.C. Berkeley. As a researcher, I had little awareness of the open science movement but now realize how much it could have positively impacted my work. One of my goals is to make it easy for researchers to learn about and incorporate open science best practices and tools into their work in order to improve the reuse and impact of their research. 

Huajin Wang, Research Liaison to Biology and Computer Science
I am a cell biologist by training and joined the University Libraries in 2017 after a PhD at University of Alberta and postdoc at Yale and Harvard. I have had extensive first-hand experience working with research data and dealing with data sharing and research reproducibility issues; the transition into librarian position offered a great opportunity to reflect more deeply on these issues. My current work focuses on building community and infrastructure for scientific data reuse and reproducibility, and training the next generation of scientists on data science tools and best practices that enhance scientific rigor and data sharing.