Sep 19-21, 2022
9:00-13:00 (Mon/Tue), 9:00-17:00 (Wed) CEST
Instructors: Florian Goth, Markus Ankenbrand
Helpers: Kerstin Schmid, Yanick Thurn, Mike Klaus, Jefferson Portela, Maximilian Pfefferle, Toby Hodges
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".
This is a pilot workshop, testing out a lesson that is still under development. The lesson authors would appreciate any feedback you can give them about the lesson content and suggestions for how it could be further improved.
Who: This lesson assumes you have a working knowledge of Python. These requirements can be fulfilled by: a) completing a Software Carpentry Python workshop or b) completing a Data Carpentry Ecology workshop (with Python) and a Data Carpentry Genomics workshop or c) independent exposure to Python. If you’re unsure whether you have enough experience to participate in this workshop, please read over this detailed list, which gives all of the functions, operators, and other concepts you will need to be familiar with.
Where: Seminar room 01.001/002, GSLS Building, Beatrice-Edgell-Weg 21, 97074 Würzburg. Get directions with OpenStreetMap or Google Maps.
When: Sep 19-21, 2022. 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).
Accessibility: We are committed to making this workshop accessible to everybody. For workshops at a physical location, the workshop organizers 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 florian.goth@physik.uni-wuerzburg.de or markus.ankenbrand@uni-wuerzburg.de 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 | Pre-workshop survey |
09:00 | Imaging Basics |
10:30 | Coffee break |
11:00 | Working with skimage |
12:30 | Wrap-up |
13:00 | END |
09:00 | Drawing |
10:30 | Coffee break |
11:00 | Histograms |
12:30 | Wrap-up |
13:00 | END |
09:00 | Blurring and Thresholding |
10:30 | Coffee break |
11:00 | Connected Components |
12:00 | Lunch break |
13:00 | Morphometrics |
14:30 | Coffee break |
15:00 | Capstone Challenge |
16:00 | Wrap-up and Feedback |
16:30 | Post-workshop Survey |
16:40 | END |
The lesson taught in this workshop is being piloted and the schedule above is just a rough estimation of the topics. But we will stick to the schedule regarding start time, end time, and breaks.
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.
The setup instructions for the Image Processing with Python workshops can be found at the workshop overview site.