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Contents

  • Hello, again!
  • Mission
  • What you can expect
  • What we expect
  • Skills
  • Toolbox
  • Resources

Lab manual

Hello, again!

This “lab manual” is intended to be a living resource of Bastos Lab information and guidelines for current and prospective lab members.

Here you will find:

  • Our mission 🌅

  • What you can expect from the team 🤝

  • What the team expects from each member 🤜🤛

  • Skills you will (further) develop 🤓

  • Our toolbox 🧰

  • Resources 📖

Explore all these topics from the left menu.

Cheers!

Mission

Our lab mission is to advance scientific knowledge in the area of integrative precision agriculture to the benefit of producers in Georgia, the Southern USA, and the world through innovative ideas and tools while training the next generation of data-savy ag leaders.

What you can expect

Lab members can expect from the team:

  • Respectful, diverse, and inclusive environment to grow as a scientist and as person

  • All ideas and opinions are not only welcomed but appreciated

  • Being both a mentee and a mentor (“mentorship is not something you can pay back, only forward”)

  • Collaborations! Among your lab members, across different research groups at UGA, with different universities, and government and industry partners

What we expect

We expect that our lab members:

  • Respect and appreciate different opinions and perspectives. We can all learn from each other

  • Seek opportunities for professional and personal growth

  • Appreciate working in teams and with other scientists

  • Be curious, resourceful, and enjoy continuous learning

  • Be excited about making an impact on science, agriculture, and people

  • Have a balance. We need to take time to not think of work and refresh our minds.

Skills

Our lab members inherently and purposefully have different backgrounds and skill sets that make each of us unique. There are some underlying skill sets that we share. Those include:

  • Curiosity, resourcefulness, learning mindset

  • Team member

  • Agricultural research training with a focus on sensors, precision management, complex data

  • Statistical programming

Toolbox

In our team, we advocate the learning and use of open-source free software whenever possible and available. Below is a list of common needs and our open-source recommendation:

  • Statistical programming language: R and Python

  • IDE: RStudio, Jupyter notebooks, Google Colab

  • Literate programming: Quarto, Rmarkdown

  • Reference management: Zotero

  • Version control: git

  • Distributed version control/cloud storage: GitHub

  • Geographical information system IDE: QGIS

  • GIS big data: Google Earth Engine

  • Website deployment: GitHub pages, Netlify

  • Internal communication: Slack

Resources

Here’s a list of some free resources, including courses, presentations, online books, and blog posts.

  • Data science in a box

  • R for Excel users

  • Illustrated intro to GitHub

  • Fay Lab Manual

  • rstudioconf2022 GitHub repo

  • STA 210: regression analysis

  • Happy git and GitHub for the useR

  • STAT 545: data wrangling, exploration, and analysis with R

  • #barbarplots

Blog made with Quarto, by Leo Bastos. License: CC BY-SA 2.0.