[link to view and download the complete syllabus]

INSTRUCTOR: Dr. Emilio M. Bruna website

CONTACT INFO: Phone: (352) 846-0634 | email: embruna@ufl.edu | Twitter: @BrunaLab

CLASS SESSIONS: Friday, Periods 6-8 (12:50-3:50) in Grinter Hall 376 and online

OFFICE HOURS: Mondays and Wednesdays from 10:30-12:00 via zoom (you can guarantee a specific time slot by scheduling online at http://brunalab.org/teaching/office-hours) OR by appointment

OBJECTIVES: This course is designed for graduate students from any discipline – social sciences, humanities, biophysical sciences – and at all stages of their graduate program. It is an introduction to methods for collecting, organizing, managing, and visualizing both qualitative and quantitative data. Students will gain hands-on experience with best practices and tools. At the conclusion of this course students will be able to:

1. Describe the different types of research data;
2. Explain the need for and benefits of data management and sharing;
3. Describe and implement best practices for the collection, storage, management, archiving, and sharing of research data;
4. Find, download, and analyze publicly available data from repositories;
5. Carry out simple and reproducible data corrections and dataset organization;
6. Describe public policies and agency requirements for data management and sharing;
7. Articulate the major legal and ethical considerations regarding the collection, use, and storage of research data (e.g., privacy/human subjects, intellectual property;
8. Create and Implement and a Data Management Plan;
9. Identify and properly use tools and techniques for more efficient and secure data collection in the field.

COURSE FORMAT: I believe there is no better way to learn than by doing, which is why this course is taught (mostly) in a ‘flipped-course’ format. Students are expected to complete each week’s assigned reading and watch the short video lectures prior class. The class session will typically include an opportunity for students to ask questions about the pre-class materials and for the instructor to briefly summarize material or demonstrate challenging concepts; occasionally there will be a class discussion about the assigned reading. However, most of the class session will be spent working in small groups on exercises that reinforce that week’s concepts and techniques. Throughout the session I will be circulating between groups to assist with the assignment, work though mistakes, and discuss how the techniques can be applied to each student’s research.

COURSE MATERIALS:

1. Required Textbook: None. All readings and materials will be provided to students on the course webpage,
2. Course Web Pages: All course materials, communication, and assignment submission will be via Canvas: https://elearning.ufl.edu/.

 Assignments:  The course grade is based on the completion of the following assignments:

1. Weekly in-class in-class exercises (14 x 20 pts each = 350 points total)
2. An individual data management project (750 points).
3. Course total: 1100 points

Due Dates:

1. In-class Assignments: Most of the in-class assignments involve hands-on practice with data collection or manipulation. In some weeks, however, assignment will be the submission of questions for group discussion or brief reflection on the issues from the readings. Most in-class assignments are designed to be completed during the class session, but to ensure students master the concepts rather than rush through them they can be submitted anytime until 9 am the following Monday.
2. Individual Project: due no later than 5 pm on the scheduled date of the final exam.