Open Science at CMU Newsletter - December 2019


In the last issue of the Open Science Newsletter of the year, we have an event report from Open Science Symposium 2019; we are excited to announce the licensing of LabArchives; we are also delighted to share many more events and workshops coming next semester that will help you to learn open science tools, data science skills, and data management best practices. 

Contact us at and follow us at #CMUOpenScience.

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Open Science Symposium 2019 Recap

On November 7, 2019, we hosted the 2nd CMU Open Science Symposium at Mellon Institute Library. Researchers, students and experts from a wide range of disciplines gathered to discuss opportunities and challenges of transparent and reproducible research. Invited speakers include researchers who shared their own projects and first-hand experience applying open science principles and tools to transform day-to-day research and improve collaboration, developers who showcased tools and platforms they develop to advance data and resource sharing, and representatives from funding agencies, research centers and publishers who shared their views on providing incentives and metrics for data sharing and reuse. In addition to invited talks, audience had engaging interactions with speakers and each other through Q&A, panel discussions, and a networking reception.  There was a consensus from all participants that in order to make science more transparent, reproducible and reusable, we need to share our data, code and protocols, we need to build better tools to ensure FAIR sharing and reproducibility,  we need to develop better data standards, we need to improve data sharing policy, and the most important of all, we need to work together to raise awareness and build a supportive open science community. 

All the slides, video recordings and Tweets (#CMUOpenScience) about the Symposium are archived and shared on Open Science Framework and on the event website. Take a look, spread the word, and be a part of the growing open science community! 

LabArchives Coming to Carnegie Mellon 

University Libraries have purchased a license for LabArchives, a electronic lab notebook (ELN) platform accessible by the entire CMU campus. The Professional Edition enables CMU researchers to organize and preserve research data, document and share lab workflow, reagents and results, both within and outside of the research group.  The Classroom Edition integrates with the existing teaching platform Canvas, and allows instructors to assign, grade, and monitor student work in classes.  

To learn more details, review instruction materials specifically developed for CMU, or attend weekly webinars provided by LabArchives, visit our LabArchives resource page
NCBI Codeathon at CMU

We are excited to host NCBI Biomedical Data Science Codeathon at Carnegie Mellon University, on January 8-10, 2020. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for large scale genomic analyses from high-throughput experiments. The event is open to anyone selected for the codeathon and willing to travel to Pittsburgh. For more details, see this blog post. Contact Ben Busby for questions.

Upcoming Workshops on Open Science and Research Data Management
CMU Libraries is offering the following workshops on Open Science and Research Data Management in the Spring semester:

Writing an Effective Data Management Plan
Hannah Gunderman
01/27/2020, 6:00 PM
This workshop will cover how to prepare an effective data management plan for a grant proposal, your own personal research, or for a research lab. We will cover all aspects of what should be included in these plans, including data collection, storage, security, and access. Register here

Data Management for Social Sciences
Hannah Gunderman and Sarah Young
02/10/2020, 6:00 PM
Researchers in the social sciences engage with unique forms of data, including surveys, ethnographic data, and census data. This workshop provides data management tips for social scientists, including cleaning data, developing filenaming schemes, and storing data securely. Register here

Terms of Service: Looking at Data Rights
Jessica Benner and Tess Wilson
02/13/2020,12:30 PM
When we check an "I Agree" box, what are we really agreeing to? What do we sacrifice for convenience and access to our digital world? Join us for an interactive workshop that examines data rights in a practical way. 

Data Visualization Basics
Emma Slayton
02/06/2020, 12:30 PM
This workshop provides an introduction to data visualization, or the techniques used to visually display or communicate data in graphs, charts and other tools. 

Data Visualization in R 
Emma Slayton
02/20/2020, 12:30 PM
This workshop provides an introduction to data visualization in R, or the techniques used to visually display or communicate data. 

Reproducible Data Visualization in Jupyter Notebooks
Huajin Wang
02/27/2020, 12:30 PM
Beginning with a short presentation on principles of computational reproducibility, followed by a hands-on live-coding session, the workshop teaches how to using Python libraries and Jupyter Notebook to make reproducible and beautiful figures. Register here

Data Management for STEM
Hannah Gunderman and Huajin Wang 
03/02/2020, 6:00 PM
Researchers in STEM disciplines engage with unique forms of data including algorithms, code, spreadsheets, and big data. This workshop provides data management tips for STEM researchers including cleaning data, developing filenaming schemes, and storing data securely, especially with large datasets. Register here

Cleaning Messy Data with OpenRefine
Sarah Young 
03/05/2020, 12:30 PM
OpenRefine is a free, open source tool to help you prepare your data for analysis. Quickly and easily transform data, split and merge columns, remove whitespace, and perform many more common data cleaning tasks. Register here

Data Visualization with Tableau
Emma Slayton
03/16/2020, 1:00:00 PM
This workshop provides an introduction to data visualization in Tableau, or the techniques used.  

You can register for workshops and see the full list of workshop offerings from University Libraries at

Save the Date: The Next Carpentries Workshop
The Carpentries – We teach foundational coding and data science skills to researchers worldwide.

Save the date for the next Carpentries workshop, March 12 - 13, 2020. The main topic of this session will be on Data Carpentries for R. Details and registration information to come! 
Use KiltHub to Share Your Publication Data

The University Libraries manage KiltHub, Carnegie Mellon University's institutional and data repository, as part of our commitment to support open dissemination of the university's research output.  Due to funder and publisher requirements, many CMU researchers need to make their data openly available to readers promptly upon publication. Depositing datasets in KiltHub allows scholars to fulfill these requirements as well as providing them with DOIs, altmetrics, and download statistics.

Several research groups have published the data supporting their articles in KiltHub this semester, here are a few examples: 

For more information on the KiltHub repository, click here. You can also email the KiltHub team or contact your department's library subject specialist for a consultation.

Research Data Collaborations Lab

We will continue piloting our Research Data Collaborations Lab (dataCoLAB) in the Spring semester. To connect the research community across disciplinary boundaries and facilitate collaborations between data producers and data scientists, we will match researchers who need help with their datasets with individuals who have data science and computer science skills to work together. Information professionals from the University Libraries will provide support on research data management and project documentation.  

If you are interested in getting help with your data, building consulting experience, finding potential collaborators, or to learn more about this program, email us at

To register as a consultant: 

To register for assistance with your data: