Data Carpentry workshops are for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data. We will cover data organization in spreadsheets, data cleaning, the command line, and R for data analysis and visualization using examples from biology. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.
Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.
Updates will be posted to this website as they become available.
Instructors: Kara Woo (Washington State University), Naupaka Zimmerman (University of Arizona)
Assistants: Matt Pruett, Peter Olsoy, Eliot Miller
Who: The course is aimed at faculty, research staff, postdocs, graduate students, advanced undergraduates, and other researchers in any field. No prior computational experience is required.
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). 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 firstname.lastname@example.org for questions and information not covered here.
Twitter: @datacarpentry #datacarpentry #dcwsu
Data Carpentry is supported by the Gordon and Betty Moore Foundation and 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 is through EventBrite, see below.
To participate in a Data Carpentry workshop, 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. Participants should bring and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.
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 is a specialized programming language used with databases. We use a simple database manager called SQLite, either directly or through a browser plugin.
OpenRefine (formerly Google Refine) is a powerful tool for exploring and working with messy data.
sqlite3 comes pre-installed on Linux.
Also install the Firefox SQLite browser plugin described below.
Download the OpenRefine software described below.
Instead of using
sqlite3 from the command line,
you may use this plugin
for Firefox instead.
To install it:
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.