Research Data Management Workshop for graduate students, Jan. 28 - Feb. 1

Research Data Management Workshop
Monday, January 28, 2019 - Friday, February 1, 2019
138 Lewis Science Library

Join us for a five-day workshop on research data management for graduate students, organized and sponsored by Princeton University Library, Princeton Institute for Computational Science and Engineering, and OIT Research Computing. Topics covered include an introduction to research data management, processing and analyzing data, and best practices for sharing and archiving research data.

Apply now by Friday, December 21, 2018.

Application: Open to all current Princeton University graduate students. Seating is limited, so advanced registration is required. Participants are expected to attend all 5 days. All participants must have an active PU NetID. A link to the registration site, along with more registration information can be found here.

If you are unable to attend the entire workshop but would still like to attend a portion of it, please email rcinfo@princeton.edu with your availability and we will add you to the wait list. If seats are available, we will do the best we can to accommodate as many participants as possible.

This event is co-sponsored by the Office of the Dean for Research, the Graduate School, the Center for Statistics and Machine Learning, and the Center for Digital Humanities.

The goals of the workshop are for graduate students to:

  • Gain new skills in research data management
  • Learn best practices and effective tools for data management
  • Understand issues related to compliance with funding agencies' data management requirements
  • Become familiar with on-campus services and resources that help with research data management 

Schedule

Day 1, January 28: Workshop Introduction and Overview of Research Data Management

1:00-2:00 p.m.  Welcome, Curt Hillegas, PICSciE/OIT Research Computing
                            Opening Remarks, Christine Murphy, Graduate School, and Dan Marlow, Physics
                            Introduction and RDM Curriculum Overview - Willow Dressel and Yuan Li, Princeton University
                            Library

2:00-2:15 p.m.   Coffee Break

2:15-3:00 p.m.   Overview of Research Data Management
                             Willow Dressel and Yuan Li

3:00-3:30 p.m.   Hands-on activities
                             Create a data management plan for your project
                             Willow Dressel and Yuan Li

3:30-3:45 p.m.   Q&A, wrap-up, and online evaluation

Day 2, January 29: Creating, Collecting, Compliance

1:00-1:45 p.m.   Data Management in the Creation and Collecting Phase
                             Willow Dressel and Anne Marie Phillips, Princeton University Library
                             Q&A

1:45-2:15 p.m.   Hands-on activities
                             File naming and folder structuring
                             Identifying types and stages of data
                             Willow Dressel and Yuan Li

2:15-2:30 p.m.   Coffee Break

2:30-3:30 p.m.   Legal and ethical considerations and special session on Human Subjects
                             Maureen Thompson-Siegel and John Jenkins, Office of Research Project Administration (ORPA)
                             Paul Hryvniak and Sheera Gaskin, Research Integrity and Assurance (RIA)
                             Wesley D. Markham, Associate University Counsel, OGC
                             Yuan Li

3:30-3:45 p.m.   Q&A, wrap-up, and online evaluation

Day 3, January 30: Processing and Analyzing Data

1:00-2:00 p.m.   Overview of Infrastructure for Storing, Moving, and Sharing Data
                             Curt Hillegas, Chris Tengi, OIT Research Computing; Bill Wichser, Princeton Institute for
                             Computational Science and Engineering (PICSciE); Martin Harriss, OIT; Natasha Ermolaev,
                            Center for Digital Humanities (CDH)

2:00-3:00 p.m.   Data Analysis Tools
                             Overview of data analysis tools, Oscar Torres-Reyna, Princeton University Library
                             Python and Pandas, Matthew Cahn, OIT Research Computing
                             Apache Spark, Ben Hicks, OIT Research Computing/CDH
                             TensorFlow TBC
                             Q&A               

3:00-3:10 p.m.   Coffee Break

3:10-4:00 p.m.   Describing, Classifying, and Protecting data
                             Ben Hicks; David Sherry, OIT; Gretchen Thiele, OIT Research Computing

4:00-4:10 p.m.   Q&A, wrap up, and online evaluation

Day 4, January 31: Publishing, Sharing and Re-Using Data

1:00-1:45 p.m.   Data Publishing, Sharing, and Reusing Data
                             Willow Dressel and Yuan Li
                             Q&A

1:45-2:00 p.m.   Hands-on activities
                             Willow Dressel and Yuan Li

2:00-2:45 p.m.   Legal and ethical considerations and compliance: Publishing, Sharing, and Re-use
                             Robert Berness and Yuan Li
                             Q&A

2:45-3:00 p.m.   Coffee Break

3:00-4:00 p.m.   Different approaches to creating and sharing data
                             April Clyburne-Sherin, Code Ocean
                             John Wiggins, Princeton Neuroscience Institute (PNI) & Matthew Cahn TBC 
                             Damian Sian, OIT

4:00-4:10 p.m.   Q&A, wrap-up, and online evaluation

Day 5, February 1: Preserving and Archiving Data

1:00-1:45 p.m.   Preserving and Archiving Data
                             Willow Dressel and Yuan Li
                             Q&A

1:45-2:15 p.m.   Hands-on activities 
                             Willow Dressel and Yuan Li

2:15-2:30 p.m.   Coffee Break

2:30-3:30 p.m.   Best practices on campus: DataSpace, Archives, Backing-up data
                             Mark Ratliff, OIT; Annalise Berdini, Princeton University Library; Gretchen Thiele, OIT
                             Research Computing

3:30-3:40 p.m.   Wrap-up and online evaluation

3:40-3:45 p.m.   Closing Remarks, Karla Ewalt, Office of the Dean for Research

3:45-4:30 p.m.   Reception, Lewis Science Library Atrium

Code of Conduct

We are committed to providing a welcoming and harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of workshop participants in any form. This code of conduct applies to all participants, including Princeton staff and applies to all modes of interaction, both in-person and online.

Princeton Research Data Management Workshop participants agree to:

  • Be considerate in speech and actions, and actively seek to acknowledge and respect the boundaries of fellow attendees.
  • Refrain from demeaning, discriminatory, or harassing behavior and speech. Harassment includes, but is not limited to: deliberate intimidation; stalking; unwanted photography or recording; sustained or willful disruption of talks or other events; inappropriate physical contact; use of sexual or discriminatory imagery, comments, or jokes; and unwelcome sexual attention. If you feel that someone has harassed you or otherwise treated you inappropriately, please alert any member of the organizing committee in person.
  • Alert a Workshop presenter/instructor or organizer if you notice a dangerous situation, someone in distress, or violations of this code of conduct, even if they seem inconsequential.
  • Abide and adhere to PU’s Rights, Rules, Responsibilities

Need help?
Please speak with Florevel (Floe) Fusin-Wischusen, floe@princeton.edu, (609) 258-8071, if you have any concerns. You may also reach out to one of the presenters.

We welcome your feedback on this and every other aspect of the Workshop, and we thank you for working with us to make it a safe, inclusive, and enjoyable experience for everyone who participates.
Parts of above text is licensed CC BY-SA 4.0. Credit to SRCCON and URSSI.

Questions? Contact rcinfo@princeton.edu.