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Applied Ecological Data Science

Analytical Thinking
Communication
Critical Thinking
Leadership & Collaboration

Course Description

Application of ecological knowledge and data science skills to conduct research using publicly available, open datasets. Students will gain experience with research techniques and tools that are applicable to a range of ecological sub-disciplines.


Athena Title

Applied Ecological Data Sci


Prerequisite

[(ECOL 3500 or ECOL 3505H) and ECOL 3500L] or [(FANR 3200W and FANR 3200L) and (ECOL 2550 or FANR 2010-2010L or STAT 2000 or STAT 2000E or STAT 2100H or BIOS 2010 or BIOS 2010E)] or permission of department


Semester Course Offered

Offered spring


Grading System

A - F (Traditional)


Student learning Outcomes

  • Understand the scientific process from experimental design to communication of your research findings
  • Organize and synthesize relevant peer-reviewed research using citation management software
  • Implement reproducible workflows and best practices for data organization, analysis, and visualization using relevant computational tools (R/RStudio, GitHub)
  • Apply team science best practices to effectively work as part of a research group
  • Effectively share your research findings with a scientific audience

Topical Outline

  • Collaboration and research ethics • Understanding the science of team science • Navigating the ethics of ecological research and statistical analysis
  • Developing scientific research questions • Conceptualizing relevant and answerable questions • Searching databases of peer-reviewed literature • Organizing literature using a citation management software • Finding open data to address your question and hypotheses
  • Data management best practices • Implementing FAIR (Findable, Accessible, Interoperable, Reusable) data principles • Reading and Writing Metadata • Developing and implementing reproducible workflows (RStudio projects, R Markdown) • Using version control (GitHub)
  • Data organization, analysis, and visualization using R/RStudio • Importing, tidying, and organizing data (tidyverse) • Visualizing data (ggplot2) • Conducting statistical analyses • Comparing expected and actual results to make inferences
  • Presenting ecological information • Writing journal-style papers • Conducting and responding to peer review • Designing and presenting scientific posters

Institutional Competencies Learning Outcomes

Analytical Thinking

The ability to reason, interpret, analyze, and solve problems from a wide array of authentic contexts.


Communication

The ability to effectively develop, express, and exchange ideas in written, oral, interpersonal, or visual form.


Critical Thinking

The ability to pursue and comprehensively evaluate information before accepting or establishing a conclusion, decision, or action.


Leadership & Collaboration

The capacity to engage in the relational process of optimizing personal and collective strengths toward a common goal.



Syllabus


Public CV