# Chapter 1 Overview

This book is intended to quickly introduce users to TERRA REF data through a series of tutorials. TERRA REF has many types of data, and most can be accessed in multiple ways. Although this makes it more complicated to learn (and teach!), the objective is to provide users with the flexibility to access data in the most useful way.

The first section walks the user through the steps of downloading and combining three different types of data: plot level phenotypes, meteorological data, and images. Subsequent sections provide more detailed examples that show how to access a larger variety of data and meta-data.

For those who are eager to see what is on deck, there are additional tutorials under development in the tutorials repository on GitHub. These can be found in the traits, sensors, and genomics subfolders. Users are encouraged to revise and contribute new content.

## 1.1 Pre-requisites

While we assume that readers will have some familiarity with the nature of the problem - remote sensing of crop plants - for the most part, these tutorials assume that the user will bring their own scientific questions and a sense of curiosity and are eager to learn.

These tutorials are aimed at users who are familiar with or willing to learn programming languages including R (particularly for accessing plot level trait data) and Python (primarily for accessing environmental data and sensor data). In addition, there are examples of using SQL for more sophisticated database queries, as well as the Bash terminal.

Some of the lessons only require a web browser; others will assume familiarity with programming at the command line in (typically only one of) Python, R, and / or SQL. You should be willing to find help (see finding help, below).

### 1.1.1 Technical Requirements

At a minimum, you should have:

• An internet connection
• Web browser
• The tutorials will state which databases you will need access to
• Software:
• Software requirements vary with the tutorials, and may be complex

### 1.1.2 Installation instructions

Option 1 The recommended and easier option is to use our VICE app on CyVerse’s Discovery Environment platform. All necessary programs and libraries are installed and accessed using RStudio. You’ll need a CyVerse account; follow instructions below to set up.

Launching TERRA REF app on VICE:

1. Click this button
3. Hit “Launch Analysis” button in pop up window, and select arrow button in Analyses window
4. Wait patiently

Reopen running TERRA REF instance:

1. Open the CyVerse Discovery Environment
3. Open Analyses window and hit arrow button to open up RStudio

Option 2 Everything necessary can be installed locally instead of using the VICE app.

You will need to install R and a handful of R packages.

All of the packages except traits are available on CRAN and can be installed using the install.packages function:

install.packages('tidyverse', 'jsonlite', 'knitr', 'lubridate', 'raster', 'sf')

Although traits is also on CRAN, you need to download the TERRA REF version from GitHub to handle larger datasets:

install.packages('devtools')
devtools::install_github('terraref/traits')

You will additionally need to install Python and the terrautils library, as below:

pip install terrautils

### 1.1.3 User accounts and permission to access TERRA REF data

The first few chapters in the ‘vignettes’ section use publicly available sample data sets. Subsequent sections are also written to use publicly available data sets, but some of the examples require data that requires users to sign up. To sign up, you will need to 1) fill out the TERRA REF Beta user questionnaire (terraref.org/beta) and 2) request access to specific databases.

## 1.2 Ways of Accessing Data

• Web Interfaces
• Clowder (sensor and genomic data)
• Globus (sensor and genomic data)
• BETYdb (trait data and experimental metadata)
• CoGe (genomic data)
• Files
• Programming APIs
• API Clients

## 1.3 Other Resources

The TERRA REF website: terraref.org

The TERRA REF Technical Documentation: docs.terraref.org