Research Workshop Series

LATIS offers a series of workshops created by our experts that are free and open to all faculty and graduate students. Join our LATIS Research Workshops Google Group to be the first to learn about workshops.

Qualitative Analysis - Coding Overview

Friday, March 2, 2018 50B Humphrey I 9:30 a.m. – 12:00 p.m. Register (new tab)

The heart of most forms of qualitative analysis involves coding: the segmentation, bucketing, sorting, tagging, or otherwise categorizing of portions of source materials. This workshop will include hands-on exercises and cover a variety of approaches to coding qualitative materials, including various types of codes and their uses, while also addressing the mechanics of how to code with highlighter & paper or using qualitative analysis software. It will focus on best practices and techniques for doing the work of coding, rather than on epistemological and ontological concerns, which are best handled by disciplinary methodologists in participants' specific fields.

Introduction to Python

Friday, March 9, 2018 131A Bruininks Hall I 9:30 a.m. – 12:00 p.m. I Register (new tab)

Python has seen wide adoption in academic research because it is a powerful but easy-to-learn programming language. In this workshop, participants will learn about the pros and cons of using Python for research computing, the fundamental building blocks and basic grammar of a Python program, and how the basic libraries of the scientific Python stack can be connected to create robust, reproducible analyses. This workshop is targeted towards grad students and other researchers who have had minimal exposure or are new to Python, though some previous scripting or programming experience (e.g., MATLAB or R) would be helpful.

Introduction to R

Friday, March 23, 2018 131A Bruininks Hall I 9:30 a.m. – 12:00 p.m. I Register (new tab)

This workshop will provide an introduction to R, a popular tool for statistical computing. Participants will learn how to get started using R for social science data, including how to read data into R, what to consider when prepping your data for R, basic data cleaning (renaming, recoding, and converting variables), basic data exploration, and how to save files manipulated in R. No experience using R is assumed. Please bring a computer to the workshop with R ( and RStudio ( installed.

Data Management in Transition: Strategies for When You Graduate

Friday, March 30, 2018 131A Bruininks Hall 9:30 a.m. – 12:00 p.m. I Register (new tab)

Research, scholarly, and creative work doesn't end with degree completion; however, access to many of the data storage tools and software that have supported their work changes when students become alumni. This workshop will help graduate students navigate questions of if and how they can take their data and materials with them when they leave. Participants will learn about University policies that guide data ownership, access changes that happen upon graduation, as well as resources, tips, and advice for planning to manage their own data and materials after they leave.

Introduction to Parallel Computing

Friday, April 6, 2018 131A Bruininks Hall I 9:30 a.m. – 12:00 p.m. I Register (new tab)

This workshop is intended to provide participants with a quick overview of the broader parallel computing landscape, including: (a) the basic nomenclature and concepts underlying parallel computing, (b) some techniques for running "embarrassingly parallel" jobs, (c) libraries such as OpenMP and OpenMPI, and (d) when it makes sense to use  accelerators (e.g., GPUs) in the parallel pipeline. While the material presented in this workshop is able to be used over a number of languages, examples and exercises will focus on parallel computing in R or Python.

Mixed Methods Analysis in NVivo

Friday, April 13, 2018 Appleby 128 I 9:30 a.m. – 12:00 p.m. I Register (new tab)

NVivo is a qualitative data management, coding and markup tool, that facilitates powerful querying and exploration of source materials for mixed methods analysis. This workshop covers the more advanced functions of NVivo, including queries and matrices that use classifications/attributes (variables) for sorting sources, importing and working with survey data from Qualtrics, organizing analysis using “cases” complete with demographic/bibliographic information, and exporting data from NVivo to a statistics package. (Basic knowledge of NVivo’s core functions is recommended.)

Introduction to SQL and Research Databases

Friday, April 27, 2018 I 9:30 a.m. – 12:00 p.m. I Register (new tab)

Text files are fine when you have thousands of observations, but what do you do when you have millions (or billions)? In this workshop, participants will learn about choices in database technology that support data at scale; the building blocks of schema design; how to write SQL queries to retrieve, delete, insert, and update data in a database; and how to connect their database to a R or Python script.