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NEON provides open ecological data from over 80 locations across the United States. NEON data cover a wide range of subject areas within ecology, including organismal observations, biogeochemistry, remote sensing, and micrometeorology. Some datasets already span several years of data collection.

This workshop will provide an introduction to discovering, accessing and preparing a variety of NEON data for your research, primarily using R. The workshop will be divided into two sections of roughly equal length.

1. The workshop will begin will be a code-along guide to NEON data, including
   a. discovering and accessing NEON data, via the  and the Application Programming Interface (API),
   b. understanding the contents and quality of various data packages, and
   c. performing common data merges, summarizations, and transformations.
   Instruction will include guidance in using R packages, including some that have been developed by NEON.
2. In the final portion, participants will divide into breakout rooms to go through coding tutorials on specific data sets of interest. There will also be one breakout room available as an open help desk/Q&A session for participants who want to explore data products of interest on their own.

Required Prior Knowledge

The workshop will assume that participants have a basic level of familiarity with working with data in R, including installing and loading packages, and data import.

Registration

Registration for this workshop is now open: . Registration is limited to 60 participants.

Workshop Schedule

All times are denoted in Eastern Daylight Time.

Workshop Instructors & Helpers

• Megan A. Jones; @meganahjones, Research Scientist, Science Education; NEON program, Battelle
• Donal O'Leary; Data Science Educator; NEON program, Battelle
• Claire Lunch; Data Scientist; NEON program, Battelle

Please get in touch with the instructors prior to the workshop with any questions.

Do you Twitter?

Please tweet at @NEON_Sci or use the hashtag #NEONData during this workshop!

Before the Workshop

To participant in this workshop, you will need a laptop with R (at least version 3.4.0), and preferably RStudio, loaded on your computer.

Prior to the workshop you should have R and, preferably, RStudio installed on your computer.

Install R & RStudio

Windows R/RStudio Install

• Run the .exe file that was just downloaded
• Under Installers select RStudio X.XX.XXX - Windows Vista/7/8/10
• Double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Mac R/RStudio Install

• Go to  and click on Download R for (Mac) OS X
• Select the .pkg file for the version of OS X that you have and the file will download.
• Double click on the file that was downloaded and R will install
• Go to the 
• Under Installers select RStudio X.XX.XXXX - Mac OS X XX.X (64-bit) to download it.
• Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Linux R/RStudio Install

• R is available through most Linux package managers. You can download the binary files for your distribution from . Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R).
• To install RStudio, go to the 
• Under Installers select the version for your distribution.
• Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Install R Packages

Please have these packages installed and updated prior to the start of the workshop.

• neonUtilities: install.packages("neonUtilities"); neonUtiltities only works with R version 3.4 or higher. For further directions, see the start of the Use the neonUtilities Package to Access NEON Data tutorial.
• raster: install.packages("raster"); to work with raster files in R.
• rhdf5: install.packages("BiocManager"), BiocManager::install("rhdf5"); to work with HDF5 files in R. This package is not on CRAN, hence the code to download from BiocManager.
• devtools: install.packages("devtools"); required to install using the install_github() function.
• geoNEON: ¾±²Ô²õ³Ù²¹±ô±ô³å²µ¾±³Ù³ó³Ü²ú("±··¡°¿±·³§³¦¾±±ð²Ô³¦±ð/±··¡°¿±·-²µ±ð´Ç±ô´Ç³¦²¹³Ù¾±´Ç²Ô/²µ±ð´Ç±··¡°¿±·â€�); to get specific location data for NEON data and samples. This package is not on CRAN, hence the code to download from GitHub.

Additional packages, if you plan to attend the NEON (aquatic) instrument data breakout session

• ggplot2: install.packages("ggplot2"); for plotting
• dplyr: install.packages("dplyr"); for select data manipulation functions
• padr: install.packages("padr"); for working with time series data

If you want to install all of them, you can use the following code.

 install.packages("neonUtilities")
 install.packages("raster")
 install.packages("devtools")
 devtools::install_github("NEONScience/NEON-geolocation/geoNEON")
 install.packages("BiocManager")
 BiocManager::install("rhdf5")

 #additional packages, if selecting the Aquatic Instrument data exercise breakout session
 install.packages("ggplot2")
 install.packages("dplyr")
 install.packages("padr")

Update R Packages

In RStudio, you can go to Tools --> Check for package updates to update previously installed packages on your computer.

Or you can use update.packages() to update all packages that are installed in R automatically.

More on Packages in R

Workshop Schedule

All times are Eastern Daylight Time