Table of Contents
General Information
The Summer Institute of 2019 brings together ten science teams for a short course on data and software skills in socio-environmental synthesis. Through hands-on tutorial and project consultation, SESYNC staff will aim to accelerate your team’s adoption of cyber resources in all phases of data-driven research and dissemination.
Participants should expect to:
- learn new scientific computing skills
- overcome specific or conceptual project hurdles
- gain coding confidence
- have fun
Instructors:
- Ian Carroll, Data Scientist
- Rachael Blake, Data Scientist
- Benoit Parmentier, Data Scientist
- Kelly Hondula, rOpenSci Fellow
When:
Tuesday, July 23, 2019 to Friday, July 26, 2019
Optional day for basic R training: Monday, July 22
Where:
1 Park Place, Suite 300
Annapolis, MD 21401
Get directions with OpenStreetMap or Google Maps.
Contact:
Please email icarroll@sesync.org with any questions or for information not covered here.
Requirements
- Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) with a full-featured browser (not Microsft Edge).
- At least one team member must bring data for the mini-project; a sample/incomplete data is okay.
- After the course, participants must complete a reimbursement form to recover allowed travel expenses.
Schedule
Nourishment will arrive at the 10:30 am break, the on-site lunch provided by SESYNC at 12:30 pm, and afternoon snacks. Participants are responsible for their own breakfast and dinner arrangements (we can make recommendations).
Software
The workshop uses RStudio and Jupyter, as well as many packages and dependencies associated with these two Integrated Development Environments (IDEs). SESYNC provides a cloud platform capable of supporting the software needs for the short course, so there is nothing for you to install in advance. During and after the course, you will be able to install any and or all of this software—it is all free and open source—on your own machines. Feel free to request assistance any time during the course with installing the listed software on your laptop.
The table and lists below should help you find the right way to install the software, depending on your operating system. Both Windows and macOS users can install from the listed “Download Site”, or by following instructions given there. Linux (and optionally macOS) users should use a package manager—your Linux distro’s native one, or Homebrew on macOS—where possible. The GDAL/OGR downloads are not essential for using spatial libraries with R installed through the given download site.
Software | Download Site | Homebrew Package(s) | Aptitude Package(s) |
---|---|---|---|
git | https://git-scm.com/downloads | git |
git |
R | https://cran.rstudio.com/ | r |
r-base |
RStudio | https://www.rstudio.com/products/rstudio/download2/ | ||
Python 3.x | https://www.python.org/downloads/ | python3 |
python3 |
Jupyter Lab | http://jupyterlab.readthedocs.io/en/stable/getting_started/installation.html | ||
GDAL/OGR | https://trac.osgeo.org/osgeo4w/ | gdal , geos |
gdal-bin 1 |
1: Ubuntu users will need to add the UbuntuGIS repository prior to running apt-get install gdal-bin
The following R packages need to be installed. Open RStudio and, for each package below, type install.packages(%package%)
at the prompt and press return. Follow all prompts.
tidyr
ggplot2
dplyr
raster
sf
sp
shiny
leaflet
rmarkdown
lme4
rstanarm
data.table
The following Python packaged need to be installed. From a command prompt, type pip3 install %package%
and press return. Follow all prompts.
jupyterlab
numpy
scipy
pandas
beautifulsoup4
census
lxml
requests
sqlalchemy
scikit-learn
mlxtend
seaborn
Acknowledgments
Portions of the instructional materials and our pedagogy are adopted from The Carpentries.