Cornell University Research Community

A Data Carpentry Workshop

Organized by Cornell Statistical Consulting Unit

Cornell University Research Community

Mann Library, Room B30A, 237 Mann Drive, Ithaca, NY
Jan 15-16, 2015
9:00 am - 5 pm

General Information

Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for managing data so that they can get more done in less time, and with less pain.

Preliminary schedule:

Day 1 morning: Better use of spreadsheets
Day 1 afternoon: Cleaning and managing data with OpenRefine, Introduction to relational databases with SQLite
Day 2 morning: Working with data in R
Day 2 afternoon: Workflows and automating repetitive tasks with command line shell

Updates will be posted to this website as they become available.

Data files for the workshop are available at the following link

The etherpad for this workshop can be found here

A static copy of the etherpad as of 5:30 on Friday after the workshop ended is here

Instructors: Erika Mudrak (CSCU), Jeramia Ory (Kings College), Emily Davenport (Cornell University)

Assistants:

Who: The course is aimed at faculty, research staff, postdocs, graduate students, advanced undergraduates, and other researchers in any field.

Where: Mann Library, Room B30A, 237 Mann Drive, Ithaca, NY. Get directions with OpenStreetMap or Google Maps. Within Mann Library, B30A Classroom is in the basement as you exit the elevators. See the floor plan .

Requirements: Data Carpentry's teaching is hands-on, so participants are encouraged to bring in and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop. (We will provide instructions on setting up the required software several days in advance, and the classroom will have computers with the software installed). There are no pre-requisites, and we will assume no prior knowledge about the tools. Participants are required to abide by Software Carpentry's Code of Conduct.

Contact: Please email mudrak@cornell.edu for questions and information not covered here.

Twitter: #datacarpentry

@cscu_Cornell

Acknowledgements & Support

Data Carpentry is a partnership of several NSF-funded BIO Centers (NESCent, iPlant, iDigBio, BEACON and SESYNC) and Software Carpentry, and is sponsored by the Data Observation Network for Earth (DataONE). The structure and objectives of the curriculum as well as the teaching style are informed by Software Carpentry.

Registration

Registration is through EventBrite, see below.

Schedule

Click here for the powerpoint with the data analysis flowchart.

Thursday	09:00	Better Use of Spreadsheets
		Refreshments will be served around 10:30.
	12:00	Lunch break (on your own)
	13:00	Cleaning and managing data with OpenRefine, Introduction to relational databases with SQLite
		Refreshments will be served around 14:30.
	16:00	Wrap-up
Friday	09:00	Working with data in R
		Refreshments will be served around 10:30.
	12:00	Lunch break (on your own)
	13:00	Workflows and automating repetitive tasks with command line shell
		Refreshments will be served around 14:30.
	16:00	Wrap-up

Setup

To participate in a Data Carpentry bootcamp, you will need working copies of the software described below. Please make sure to install everything (or at least to download the installers) before the start of your bootcamp. For this bootcamp, computers in the library classroom will also be setup with the software in case a personal laptop is not available. However, participants are encouraged to bring and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.

Overview

Editor

When you're writing scripts or text, 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. (This will lose any unsaved changes to the file.)

The Bash Shell

Bash is a commonly-used shell. Using a shell gives you more power to do more tasks more quickly with your computer.

R

R is a programming language that specializes in statistical computing. It is a powerful tool for exploratory data analysis. To interact with R, we will use RStudio, an interactive development environment (IDE).

SQL

SQL is a specialized programming language used with databases. We use a simple database manager called SQLite, either directly or through a browser plugin.

OpenRefine

OpenRefine (formerly Google Refine) is a powerful tool for exploring and working with messy data.

Windows

Editor

Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). Please ask your instructor to help you do this.

Git Bash

Install Git (version control) and a Bash shell for Windows from the msysGit project's homepage. This will provide you with Bash in the Git Bash program.

Software Carpentry Installer

Other tools used in Data Carpentry have been packaged up by Software Carpentry in an installer. This installer requires an active internet connection.

Download the installer.
Double click on the file to run it.
Accept all defaults.

R

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.

SQLite

Install the Firefox SQLite browser plugin described below.

OpenRefine

Download the OpenRefine software described below.

Mac OS X

Bash

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). You may want to keep Terminal in your dock for this workshop.

Editor

We recommend Text Wrangler or Sublime Text. In a pinch, you can use nano, which should be pre-installed.

R

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

SQLite

sqlite3 comes pre-installed on Mac OS X. Also install the Firefox SQLite browser plugin described below.

OpenRefine

Download the OpenRefine software described below.

Linux

Bash

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.

Editor

Kate is one option for Linux users. In a pinch, you can use nano, which should be pre-installed.

R

You can download the binary files for your distribution from CRAN. Or you can use your package manager, e.g. for Debian/Ubuntu run apt-get install r-base. Also, please install the RStudio IDE.

SQLite

sqlite3 comes pre-installed on Linux. Also install the Firefox SQLite browser plugin described below.

OpenRefine

Download the OpenRefine software described below.

Miscellaneous

Firefox SQLite Plugin

Instead of using sqlite3 from the command line, you may use this plugin for Firefox instead. To install it:

Start Firefox.
Go to the plugin homepage.
Click the "Add Now" button.
Click "Install Now" on the dialog that appears after the download completes.
Restart Firefox when prompted.
Select "SQLite Manager" from the "Tools" menu.

OpenRefine

Head to the OpenRefine download page for information on how to install it. It will run through a browser, but will not need to use an internet connection, and your data will also be securely stored on your own computer.