Data management workshop series Fall 2022
Hosted by the University Libraries
Free to U of M graduate students
Keep your research organized by learning data management skills! Join us this fall for a series of workshops to build and enhance your data management strategies. Topics will range from introductory skills to specific tool-based workshops on citation managers, backup workflows, writing your dissertation with R, and publishing your data. Sign up for a single workshop or join us for the entire series.
Workshops will be held online via Zoom. Learn more about each workshop and register below.
There will be an opportunity to earn a Foundations of Data Management Badge by attending at least 3 out of 5 of the workshops below and completing assignments in the associated asynchronous Data Management Canvas course. Students are encouraged to self-enroll in the Canvas course to access asynchronous content AND slides/recordings of past workshops.
Sponsored by the University Libraries, LATIS, the Graduate School, OVPR, and the Informatics Institute.
Questions? Contact firstname.lastname@example.org
Data management topics and tools: An introduction to data management
August 25, 2022 | 10am - noon
Join us for a workshop introducing topics and tools to help you manage your research data. This workshop will kick off our series of data management workshops over the fall semester. This introductory workshop will build upon topics covered in the asynchronous Canvas course, present issues specific to data management for STEM and liberal arts researchers, and give a preview of tools for managing a variety of data across your entire research project.
Tools for organizing PDFs and article citations
September 19, 2022 | 10am - noon
Citation managers are tools to help you collect, organize, cite, and share research. This session will give overviews of Zotero, a free, easy to use citation manager, and EndNote, a paid, high-powered citation manager. After an introduction to both to help you decide which one will work best for you, we will split into two breakout rooms where you will learn how to set up your citation manager and use it to collect and organize citations, PDFs, and other files. We will also demonstrate how to format citations in a variety of styles and how to add in-text citations to Microsoft Word and Google Docs, as well as share citations with others using the group feature.
Storage, back-up, and versioning, oh my!
October 3, 2022 | 10am - noon
Going beyond the best practices of "3-2-1", this session will demonstrate real workflows and tools for backing up and versioning your research data. We will cover a variety of techniques for protecting your data, from low/no tech to more technical coding based tools, such as Github. No matter what your discipline or what materials you work with, this workshop will assist you in finding a storage strategy that is right for you!
Writing your thesis or dissertation with R Markdown, GitHub, and friends
October 24, 2022 | 10am-noon
The R ecosystem can be used for more than statistical analysis! This session will demonstrate how to use RStudio, R Markdown documents, and git/GitHub version control to write your thesis or dissertation in a fully reproducible and transparent way. We will cover set-up, handling citations, incorporating code and analysis, version control, and output options for your beautiful, reproducible documents (PDF, Word, HTML).
Publishing (with) data
November 14, 2022 | 10am- noon
This session will help you form good practices as you prepare to submit your research to a journal and affiliated data to a repository. Attendees will learn how to make informed decisions about where to publish by learning how to select appropriate journals and how to advocate for yourself and your research throughout the publication process.
Funders and journals also increasingly require that articles are published alongside the associated data. Learn more about what goes into sharing data with thorough documentation, in accessible formats, how to evaluate if a repository is a good fit for your data, and resources for additional support.