Community Data Science Workshops

The Community Data Science Workshops (CDSW) are a series of workshops designed to introduce some of the basic tools of programming and analysis of data from online communities to absolute beginners.

The CDSW have been held three times in Seattle in Spring and Fall 2014 and Spring 2015. So far, more than 50 people have volunteered their weekends to teach more than 200 people to program in Python, to build datasets from Web APIs, and to ask and answer questions using these data.

The following links are to the curriculum we used so that others can build on and learn:


 * Community Data Science Workshops (Spring 2016) — along with many subpages
 * Community Data Science Workshops (Fall 2015) — along with many subpages
 * Community Data Science Workshops (Spring 2015) - along with many subpages
 * Community Data Science Workshops (Fall 2014) - along with many subpages
 * Community Data Science Workshops (Spring 2014) - along with many subpages

If you would like to be notified about upcoming workshop series, please subscribe to our announcement email list. The list will get no traffic except for announcements of an upcoming CDSW.

Overview


The Community Data Science Workshops are a series of project-based workshops for anyone interested in learning how to use programming and data science tools to ask and answer questions about online communities like Wikipedia, Twitter, free and open source software, and civic media.

The workshops are for people with no previous programming experience. The goal is to bring together both researchers and academics as well as participants and leaders in online communities. The workshops have all been free of charge and are open to the public.

The sessions are schedule for one Friday evening and three Saturdays all day. Each session involves a period for lecture and technical demonstrations in the morning. This is followed by a lunch. The rest of the day consists of self-directed work on programming and data science projects supported by more experienced mentors.

Our goal is that, after the three workshops, participants will be able to use data to produce numbers, hypothesis tests, tables, and graphical visualizations to answer questions like:


 * Are new contributors to an article in Wikipedia sticking around longer or contributing more than people who joined last year?
 * Who are the most active or influential users of a particular Twitter hashtag?
 * Are people who participated in a Wikipedia outreach event staying involved? How do they compare to people that joined the project outside of the event?

Our very first workshops was originally modeled after the Boston Python Workshop but most our curriculum is brand new and has been developed and modified by the mentors and with feedback from the participants.

Put on your own CDSW
A number of people have expressed interest in putting on their own CDSW or using our curriculum. For example, the Python Workshops for Beginners organized in Waterloo in Fall 2014 were largely based on our curriculum.

If you are interested in doing something like this, we've put together some reflections and resources that might be of interest to you:


 * CDSW Spring 2014 post-mortem blog post
 * Community Data Science Workshops (Spring 2014)/Reflections — Raw notes from the mentors and organizers
 * Community Data Science Workshops (Fall 2014)/Reflections — Raw notes from the mentors and organizers

Organizers and Sponsors
Curriculum for the workshops have been developed by Benjamin Mako Hill, Ben Lewis, Frances Hocutt, Jonathan Morgan, Mika Matsuzaki, Tommy Guy. The events are only possible with the help of a long list of over 40 volunteer mentors across the two events. The workshops have been designed with lots of help and inspiration from Shauna Gordon-McKeon and Asheesh Laroia of OpenHatch and lots of inspiration from the Boston Python Workshop.

Our previous workshops have with space and funding by the University of Washington Department of Communication and the eScience Institute.

If you have any questions, contact Benjamin Mako Hill at makohill@uw.edu.