The Complete Course Syllabus can be found here.

Course Materials will be posted on the course web page: https://las6292.netlify.app/

Zoom Link for Office Hours: Tuesday & Thursday 10:30-12:00: Zoom Link

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: Tuesdays and Thursdays from 10:30-12:00 in the Tropical Ecology & Conservation Lab (711 Newell Dr.) or via zoom (you can guarantee a specific time slot by scheduling online at https://embruna.youcanbook.me/) 

OBJECTIVES: This course is a practical introduction to methods, tools, and best practices for collecting, organizing, managing, and visualizing qualitative and quantitative data. It is designed for graduate students from all disciplines at any stage of their program. At the conclusion of the 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 data set organization;
6. Describe public policies and agency requirements for data management and sharing;
7. Articulate the major legal and ethical considerations regarding data collection, use, and storage (e.g., privacy/human subjects, intellectual property, international law);
8. Create and Implement Data Management Plan in funder-specific formats;
9. Identify and properly use tools for more efficient and secure data collection in the field.

COURSE FORMAT: This course is taught (mostly) as an active-learning workshop. Students are expected to complete reading or watch some short video lectures prior class. The in-class session will typically include an opportunity to ask questions about the pre-class materials and for me to demonstrate challenging concepts; occasionally there will be a class discussion about the reading. Most of the session, however, will be spent working - sometimes in groups, sometimes individually - on exercises that reinforce the session’s concepts and techniques. During class I will be circulating between groups to assist with the assignment, work though mistakes, and discuss how the techniques can be applied to your research.

COURSE MATERIALS:

1. Required Textbook: None. All readings and materials will be provided to students on the course webpage,
2. Course Web Pages: Course materials, communication, and assignment submission will be via Canvas (https://elearning.ufl.edu) and the class website (https://las6292.netlify.app/)

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

1. Weekly in-class exercises (700 points total): 14 exercises x 50 points each. 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. Data Management Plan (200 points): due no later than 5 pm on 1 April 2022
3. Individual Data Cleanup Project (600 points): due no later than 5 pm on 29 April 2022 (scheduled date of the final exam).
4. Additional details can be found at https://las6292.netlify.app/docs/assignments/