08 - 09 Feb, 2018
9:00 am - 16:30 pm
Instructors: Margareth Gfrerer, Mesfin Diro
Helpers: Dagim Yoseph, Behailu Korma, Bonny Adane
Data Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. 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 "Best 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.
When: 08 - 09 Feb, 2018. Add to your Google Calendar.
Requirements: Participants must bring a laptop 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). They are also required to abide by Data Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organisers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email firstname.lastname@example.org for more information.
Please be sure to complete these surveys before and after the workshop.
|Morning||Data organization in spreadsheets|
|Data organization in OpenRefine|
|Afternoon||Introduction to R|
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
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.
To participate in a Data Carpentry workshop, you will need working copies of the software described below. Please make sure to install everything and try opening it to make sure it works before the start of your workshop. If you run into any problems, please feel free to email the instructor or arrive early to your workshop on the first day. Participants should bring and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.
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.
For this workshop you will need a spreadsheet program. Many people already have Microsoft Excel installed, and if you do, you're set! If you need a spreadsheet program, there are a few other options, like OpenOffice and LibreOffice. Install instructions for LibreOffice, which is free and open source, are here.
OpenRefine (previously Google Refine) is a tool for data cleaning that runs through a web browser, and any browser - Safari, Firefox, Chrome, Explorer - should work fine. You will need to download OpenRefine and install it, and when you open it, it will run through the browser, but you don't need an internet connection, and the data will all be stored on your computer.
In the workshop, we will use RStudio. RStudio is a nice interface to the programming language R. To use RStudio, you need to install both R and RStudio.
sudo apt-get install r-base, and for Fedora run
sudo yum install R) but make sure that you have at least R 3.2.2 (as pre-packaged versions might be out of date).
sudo dpkg -i rstudio-x.yy.zzz-amd64.debat the terminal).