Mar 25-26, 2023
March 25: 9:00 am - 5:00 pm EDT
(1:00 pm - 9:00 pm UTC)
March 26: 11:00 am - 5:00 pm EDT
(3:00 pm - 9:00 pm UTC)
Instructors: R. N. Uma, Ammar Alkhaldi, Jennifer Anne Wood Stubbs
Helpers: Debzani Deb, Charles Mickle, Brixx John-Garcia Panlaqui, Kiayia Propst
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. 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 "Good Enough Practices for Scientific Computing".
Who: The course is aimed at graduate students and other researchers. 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 25-26, 2023. 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 firstname.lastname@example.org or email@example.com for more information.
Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.
Who can attend?: This workshop is for a group of faculty, selected through application solicitation and peer review, affiliated with Winston-Salem State University. Others, please contact the host, Dr. Debzani Deb, listed under "Contact".
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|
|9:00 - 9:30||Welcome, Introductions, and Ice-Breaker|
|9:30 - 10:45||Introduction to R|
|10:45 - 11:00||Break|
|11:00 - 12:00||Introduction to R (continued)|
|12:00 - 1:00||Lunch|
|1:00 - 2:30||Introduction to R (continued)|
|2:45 - 3:00||Break|
|3:00 - 5:00||Continuation of R: Data Wrangling|
|END OF DAY 1|
|11:00 - 12:00||Continuation of R: Data Analysis & Visualization|
|12:00 - 1:00||Lunch|
|1:00 - 2:45||Continuation of R: Data Analysis & Visualization|
|2:45 - 3:00||Break|
|3:00 - 4:45||OpenRefine for Data Cleaning|
|4:45 - 5:00||Post-workshop survey|
|END OF WORKSHOP|
To participate in a Data Carpentry workshop, you will need access to software as 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.
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:
The setup instructions for the Data Carpentry Social Sciences workshops (with R) can be found at: R and RStudio, OpenRefine, and datasets (we will use the SAFI_clean.csv and SAFI_openrefine.csv datasets in this workshop - you can download the zip file from this link under the Data section).