March 7-8, 2018
9:00 am - 4:30 pm
Instructors: Rebecca Dikow, James Holmquist, Matt Kweskin, Holly Little
Helpers: Vanessa Gonzalez, Mike Trizna, Sue Zwicker, Mauro Lepore
Data Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".
Who: The workshop is for Smithsonian badge holders working with research data. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Where: Contees Wharf Rd., Edgewater, MD 21037. Get directions with OpenStreetMap or Google Maps.
Room: Matthias 1013
When: March 7-8, 2018, 9:00 am - 4:30 pm. Attendees must attend entire workshop. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email SI-DataScience@si.edu for more information.
Surveys
Please be sure to complete these surveys before and after the workshop.
09:00 | Introduction, Set-Up |
9:30 | Data Organization in Spreadsheets |
10:30 | Coffee |
10:45 | Data Cleaning with OpenRefine |
12:00 | Lunch break |
13:00 | Introduction to R |
14:30 | Coffee |
16:30 | Wrap-up |
09:00 | Continuation of R: data analysis and visualization |
10:30 | Coffee |
12:00 | Lunch break |
13:00 | Data management with SQL |
14:30 | Coffee |
16:30 | Wrap-up |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager (e.g. for Debian/Ubuntu
run sudo apt-get install r-base
and for Fedora run
sudo dnf install R
). Also, please install the
RStudio IDE.
For this lesson you will need OpenRefine and a web browser. Note: this is a Java program that runs on your machine (not in the cloud). It runs inside a web browser, but no web connection is needed.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It will not run correctly in Internet Explorer.
Download software from http://openrefine.org/
Create a new directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory by right-clicking and selecting "Extract ...".
Go to your newly created OpenRefine directory.
Launch OpenRefine by clicking google-refine.exe
(this will launch a command prompt window, but you can ignore that - just wait for OpenRefine to open in the browser).
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It may not run correctly in Safari.
Download software from http://openrefine.org/.
Create a new directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory by double-clicking it.
Go to your newly created OpenRefine directory.
Launch OpenRefine by dragging the icon into the Applications folder.
Use Ctrl-click/Open ...
to launch it.
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser.
Download software from http://openrefine.org/.
Make a directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory.
Go to your newly created OpenRefine directory.
Launch OpenRefine by entering ./refine
into the terminal within the OpenRefine directory.
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
SQL is a specialized programming language used with databases. For this lesson you will use DB Browser for SQLite.
Download the Windows installer from http://sqlitebrowser.org/ Most systems will use the 64-bit version, but if your computer is using a 32-bit version of Windows, you will need the 32-bit installer.
Run the .exe file that is downloaded to start the installer. Note: you will need administrative privileges to successfully install.
Choose all the default options in the installer screens.
"DB Browser for SQLite" will now be available in your Start Menu.
Download the Mac .dmg file from http://sqlitebrowser.org/
Open the .dmg file by double-clicking it.
Drag the "DB Browser for SQLite" icon to your Applications folder
For Ubuntu based systems run the following commands entering your account's password when prompted:
sudo add-apt-repository -y ppa:linuxgndu/sqlitebrowser
sudo apt-get update
sudo apt-get install sqlitebrowser
For other Linux distributions, please email SI-DataScience@si.edu for assistance
Below are optional installations that may make your life a bit easier in the future. They are useful, but not necessary for this workshop.
Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.
cmd
and press [Enter])setx HOME "%USERPROFILE%"
SUCCESS: Specified value was saved.
exit
then pressing [Enter]This will provide you with both Git and Bash in the Git Bash program.
The default shell in all versions of Mac OS X is Bash, so no
need to install anything. You access Bash from the Terminal
(found in
/Applications/Utilities
).
See the Git installation video tutorial
for an example on how to open the Terminal.
You may want to keep
Terminal in your dock for this workshop.
The default shell is usually Bash, but if your
machine is set up differently you can run it by opening a
terminal and typing bash
. There is no need to
install anything.
When you're writing code, it's nice to have a text editor that is
optimized for writing code, with features like automatic
color-coding of key words. The default text editor on Mac OS X and
Linux is usually set to Vim, which is not famous for being
intuitive. if you accidentally find yourself stuck in it, try
typing the escape key, followed by :q!
(colon, lower-case 'q',
exclamation mark), then hitting Return to return to the shell.
nano is a basic editor and the default that instructors use in the workshop. To install it, download the Data Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.
Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.
nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.
Others editors that you can use are Text Wrangler or Sublime Text.
nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.
Others editors that you can use are Gedit, Kate or Sublime Text.