General Information

More information about this workshop available at: https://github.com/datacarpentry/2015-04-23-stanford/wiki/Stanford-Data-Carpentry-2015-04-23

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.

Preliminary schedule:

• Day 1 morning: Data organization in spreadsheets and data cleaning with OpenRefine
• Day 1 afternoon: Introduction to R
• Day 2 morning: Data analysis and visualization in R
• Day 2 afternoon: Introduction to databases, combining and querying data using SQL

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

Instructors: Amy Hodge, Tracy Teal

Assistants: Katie Planey, Maude David, Keyla Badillo, Mari Muraki

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, 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 amyhodge@stanford.edu for questions and information not covered here.

Twitter: #datacarpentry

Acknowledgements & Support

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

Registration is through EventBrite, see below.