Data Analytics Research Training Fellowship*

For more information on this course, or to schedule, please contact Peace Ossom-Williamson at peace@uta.edu.

The DART Fellowship is a 6-week cohort training and development program, providing a guided pathway for information professionals to acquire data literacy skills using common methodologies applied toward discipline-specific efforts. Throughout the program, the cohort will work collaboratively with guiding researchers – professionals currently engaged in the work the participants are learning – in order to complete a major component of a research project to be published in an official presentation, article, blog, or another professional dissemination method. The guiding researchers will provide a project from which the participants can choose a component to work on.

The first week, participants will attend a two-day in-person training along with their mentors to learn the basic use of data tools in order to improve their ability to attain data literacy competencies during online trainings. They will also complete team-building exercises to develop a cohort network. Following this training are five online modules that cover sources of public health data and statistics, analytics methods and tools, and their use in public health research, and best practices in presenting data effectively. 

Course URL: https://library.uta.edu/scholcomm/research-data/dart-fellowship 

Learning Objectives:

  • Locate federal, state, and local data sources on a particular public health topic
  • Distinguish between common public health research methods
  • Clean and restructure a dataset for a chosen analysis/visualization tool
  •  Analyze data using descriptive statistics and common data manipulation techniques
  • Present reproducible findings using best practices in documentation, visualization, and reporting

Agenda:

In Person

-Day 1

  • 8-8:30 Welcome & introductions, about the program
  • 8:30-10 Presentation: Role of data in public health research and practice
  • 10-12 Presentation: Tidy data & intro to public health research design
  • 12:15-1:30 Lunch discussions
  • 1:30-5 Hands-on: Intro to SPSS (running tests, reproducibility & reporting findings)

-Day 2

  • 8-8:15 Housekeeping
  • 8:15-10 Presentation: Intro to other common tools (SAS, STATA, etc.)
  • 10-11 Presentation: Role of big data and programming
  • 11-12:15 Getting started with Git
  • 12:15-1:30 Lunch discussions
  • 1:30-5 Intro to R or Python
  • 5-5:30 Save to GitHub/Wrap-Up

 

Online Modules

  • Week 1: About data librarianship
    • Introduction to common terms
    • Data types and basic data management
  • Week 2: data cleaning and structure
  • Week 3: Quantitative methods in public health
  • Week 4: Compiling and visualizing findings
  • Week 5: End
    • Work on final projects
    • (optional) data curation/repositories

MLA CE Credits: 4