Use R to download data from the LTER data repository, the CUAHSI data center, and the GLEON DataONE member node.
Learn the basics of Metadata
Use the R package EML do develop metadata formatted in the Ecological Metadata Language
Upload data and metadata to the GLEON DataONE member node (demonstration only, due to current log-in changes in DataONE)
Aggregate data the easy way, using dplyr and tidyr
Become familiar with R package Lake Metabolizer. Contains a variety of methods for calculating lake metabolism from buoy data.
Build a Shiny App. Shiny is a web application framework for R, which you can use to turn your R code an interactive application.
1. Download and install R.
This is achieved using a CRAN mirror, such as: http://cran.stat.sfu.ca/
-Or-
Update R, if you are using an R version < 3.2.4
2. Download and install RStudio
We will be using RStudio for all examples/demonstrations. Please have the RStudio application on your laptop.
https://www.rstudio.com/products/rstudio/download/
3. Install R packages
The following packages should be installed on your computer. To install packages in R, use the following code:
install.packages(‘shiny’)
Please install:
LakeMetabolizer
rLakeAnalyzer
shiny
dataone
devtools
rmarkdown (this will install several other packages)
tidyr
dplyr
lubridate
readr
WaterML
Some packages are not yet available on CRAN. You can install packages directly from github using the devtools package. We will be using the EML package (this is installed from github, which means that you’ll need to install devtools first and then issue the command:
devtools::install_github("ropensci/EML")
Instructions are at: https://github.com/ropensci/EML
4. Download Data for the Workshop
Sparkling Lake, Wisconsin, 1-minute buoy data. We will be working with these during the workshop.
Sparkling Lake, Wisconsin, hourly buoy data. These are for reference. We will be making these during the workshop.
Shiny template files. Please download.
Shiny Tutorial: http://shiny.rstudio.com/tutorial/
Shiny App Gallery: http://shiny.rstudio.com/gallery/
Data wrangling cheatshet: https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf
Data processing with tidyr and dplyr https://rpubs.com/bradleyboehmke/data_wrangling
Schedule, July 4th, 2016
7:00-8:30 |
Breakfast |
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8:30-9:00 |
Introduction to GSA (led by GSA co-chairs) |
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9:00-11:00 |
Download data from a repository Prepare data for analysis Run Analysis using Lake Metabolizer |
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11:00-11:30 |
Break |
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11:30-13:00 |
Prepare EML metadata for harmonized data product (upload data back to repository - demonstration only due to log in credentials needed) |
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13:00-14:00 |
Lunch! |
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14:00-15:30 |
How to build a shiny app to view buoy data. (Recommended for intermediate and advanced R users) |
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15:30-16:00 |
Wrap-up, evaluations |
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16:30-17:30 |
Sport activities with students (soccer, frisbee, walking/hiking) |
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18:00-19:30 |
GLEON/NETLAKE Welcome and mixer (Welcome Paul/Kathie/Eleanor/Bas) (CCC to introduce an ice breaker Liz, Ian and Steven). |
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19:30 |
GLEON/NETLAKE Dinner |
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