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Data Management Workshop 2019

August 2, 2019

BYU Harold B. Lee Library

1:00-4:00 pm

Choose from multiple sessions and learn the ins and outs of research data management!

Register for up to three individual sessions for free at the links below.

 

Data Management Principles 101

1:00-1:50 pm

Building consistent data management practices is critical for any researcher and helps ensure you can navigate your data and various documents now and in the future. Bring your laptop and come prepared for discussion and hands-on activities.

https://open.umn.edu/otn/workshops/data-management-principles-101

 

Introduction to Git

1:00-1:50 pm

Learn the basics of using Git, a version-control system for tracking changes to files. Emphasis will be on using Git in a research data management context. No prior knowledge needed.

https://open.umn.edu/otn/workshops/introduction-to-git

 

Safeguarding Your Data

2:00-2:50 pm

Learn about ways to ensure your data remains safe and available to yourself and others. Get to know ScholarsArchive, pick up some pro tips for working with Box, and learn about data repositories for your discipline.

https://open.umn.edu/otn/workshops/safeguarding-your-data

 

Introduction to OpenRefine

2:00-2:50 pm

OpenRefine is an interactive data transformation tool. Learn the basics of data profiling (assessing the current state of your data) and data cleaning (correcting errors, removing blanks, etc).  No prior knowledge needed.

https://open.umn.edu/otn/workshops/introduction-to-openrefine

 

Sharing Your Data and Research

3:00-3:50 pm

Learn how to add your research to BYU’s institutional repository and obtain a shareable link for your work. Find out how copyright and Creative Commons licensing can help you to both share and protect your work.

https://open.umn.edu/otn/workshops/sharing-your-data-and-research

 

Introduction to Regular Expressions

3:00-3:50 pm

Learn about regular expression search patterns (regex) and how to use them to validate data and perform find and replace operations on data. No prior knowledge needed.

https://open.umn.edu/otn/workshops/introduction-to-regular-expressions