Online
Mar 16-19, 2021
9:00 - 13:00 Pacific Time
Instructors: Rohit Goswami, David DeFranza, Annajiat Alim Rasel, Scott Peterson
Helpers: Mike Davidson, Tess Grynoch
Library Carpentry is made by people working in library- and information-related roles to help you:
Library Carpentry introduces you to the fundamentals of computing and provides you with a platform for further self-directed learning. For more information on what we teach and why, please see our paper "Library Carpentry: software skills training for library professionals".
Who: The course is for people working in library- and information-related roles. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting.
When: Mar 16-19, 2021. Add to your Google Calendar.
Requirements: Participants must have access to a computer 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).
Accessibility: We are dedicated to providing a positive and accessible learning environment for all. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you.
Contact: Please email j.vandervolgen@utah.edu or annajiat@gmail.com for more information.
Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.
Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Please be sure to complete these surveys before and after the workshop.
| Before Starting | Pre-workshop survey |
| 09:00 | Jargon Busting, A Computational Approach, Introduction to Working with Data (Regular Expressions) |
| 10:30 | Tidy data for librarians |
| 13:00 | END |
| 09:00 | OpenRefine |
| 13:00 | END |
| 09:00 | Introduction to R |
| 10:30 | Starting with Data R |
| 13:00 | END |
| 09:00 | Data cleaning and Transformation with dplyr |
| 10:30 | Data Visualization with ggplot2 |
| 13:00 | END |
| 13:00 | Post-workshop survey |
To participate in a Library 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.
Please note, we expect that the R lesson setup instructions have been completed for the latter half of the workshop.
If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.
Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:
Spreadsheets are useful for data entry and data organization, and some subsetting and sorting of the data as well as getting an overview of the data. Please find instructions to install it and the data used in the lesson in the lesson.
OpenRefine is a tool to clean up and organize messy data. Please find instructions to install it and the data used in the lesson in the lesson.
R is more of a programming language than just a statistics program. It was started by Robert Gentleman and Ross Ihaka from the University of Auckland in 1995. They described it as “a language for data analysis and graphics.” You can use R to create, import, and scrape data from the web; clean and reshape it; visualize it; run statistical analysis and modeling operations on it; text and data mine it; and much more. The term “R” is used to refer to both the programming language and the software that interprets the scripts written using it. RStudio is a user interface for working with R. It is called an Integrated Development Environment (IDE): a piece of software that provides tools to make programming easier. RStudio acts as a sort of wrapper around the R language. You can use R without RStudio, but it’s much more limiting. RStudio makes it easier to import datasets, create and write scripts, and makes using R much more effective. RStudio is also free and open source. To function correctly, RStudio needs R and therefore both need to be installed on your computer. Please find setup instructions in the lesson.