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University of Texas University of Texas Libraries

Data & Donuts

Current Semester Schedule

Data & Donuts is a workshop series organized each semester by the UT Libraries Research Data Services team. Instructors from UT Libraries and partners across campus share expert advice, resources, and tools that will help you take good care of your data through all phases of the research lifecyle, from project planning to data preservation.

If you would like to be receive occasional announcements about Data & Donuts workshops and other similar events, please visit https://utlists.utexas.edu/sympa/subscribe/research-data-services to subscribe to the UT Libraries Research Data Services email list.

donut graphicWorkshops on select Fridays at 12pm via Zoom*
*see individual Zoom links for each workshop below

Please consider attending the upcoming workshops below. If you are interested in presentation slides, Zoom recordings, and other materials from past events you can access these resources at https://guides.lib.utexas.edu/data-and-donuts/information-about-past-workshops
Fall 2022
Managing Data with SQL and Relational Databases
Instructor: Michael Shensky
Date: 9/2/2022 (Fri.)
Time: 12:00 - 1:15p.m.
Location: Zoom (Virtual Workshop)
Recording: Watch in Zoom
Downloads: Presentation Slides
This workshop will provide an introduction to using SQL (Structured Query Language) to store and manage data in a relational database. Gaining familiarity with SQL can help researchers better manage large datasets, construct detailed data queries, and utilize SQL dependent filtering functionality in applications like GIS software.
Intro to Python for Data Management (In-Person/Virtual)donut graphic
Instructor: Michael Shensky
Date: 9/16/2022 (Fri.)
Time: 12:00 - 1:15p.m.
Location: PCL Learning Lab 1 &
via Zoom
Recording: Watch in Zoom
Downloads: Presentation Slides
Downloads: Python Demo (Google Colab)
When you start working with large datasets or need to develop reproducible workflows, the ability to develop scripted processes for data processing and analysis can be essential. Tune in for this workshop to learn the basics of using Python, a popular free and open source scripting language, to process and manage research data. This will be the first in-person workshop since the start of the pandemic and donuts will be provided!
Intro to R and R Studio
Instructors: Meryl Brodsky &
Hannah Chapman Tripp
Date: 9/30/2022 (Fri.)
Time: 12:00 - 1:15p.m.
Location: Zoom (Virtual Workshop)
Recording: Watch in Zoom
Downloads: Intro Slides
This workshop is a basic introduction to R and RStudio. It assumes no prior knowledge of R or programming. We ask that participants download R and then RStudio prior to the start of this workshop so that you can participate in a few active learning exercises throughout the session. For a more detailed workshop description and software installation instructions please see the following workshop overview document.
Python for Data Retrieval and Visualization
Instructors: Ian Goodale & Michael Shensky
Date: 10/14/2022 (Fri.)
Time: 12:00 - 1:15p.m.
Location: Zoom (Virtual Workshop)
Registration: Click Here to Sign Up
In this workshop you will have a chance to gain experience using Python to retrieve data from different online sources that you can utilize in your research. After retrieving data using APIs, you will learn how to process and clean the data for further analysis and visualization using pandas and matplotlib.
Data Publishing and Preservation
Instructors: Meryl Brodsky and Michael Shensky
Date: 10/28/2022 (Fri.)
Time: 12:00 - 1:15p.m.
Location: Zoom (Virtual Workshop)
Registration: Click Here to Sign Up
This workshop will discuss important considerations for researchers who are looking to preserve and publish their data. It will also highlight specific repositories that you can make use of to satisfy data preservation requirements and support open science. During the workshop we will demonstrate how to use the Texas Data Repository and discuss how to link deposited data to items in Texas ScholarWorks.

Workshop Questions

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Michael Shensky
(he/him)

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