Community Data Science Workshops

Click here for details and to sign up for announcements about upcoming Community Data Science Workshops in Seattle.

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 five 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. Through these workshops we've also collected some mentoring tips.

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

Community Data Science Workshops (Winter 2020) — along with many subpages
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 — Notes and reflections from the mentors and organizers
Community Data Science Workshops (Fall 2014)/Reflections — Notes and reflections from the mentors and organizers
Community Data Science Workshops (Fall 2015)/Reflections — Notes and reflections 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, and Dharma Dailey. 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.

Courses

We have also taught a series of University courses based on this curriculum. These include:

[Spring 2017] COM597I: Community Data Science: Programming and Data Science for Social Media — A quarter-long course taught by Tommy Guy that adapts and builds upon the CDSW curriculum to teach introductory programming and data science to absolute beginners in the context of the University of Washington's Communication Leadership program.
[Spring 2016] HCDE598: Data Science for User Experience Researchers (DS4UX): A special topics course in the "Masters in Human-Centered Design & Engineering" program covering the use of data science tools and concepts to conduct research with open online data taught by Jonathan Morgan.
[Spring 2016] COM597: Community Data Science: Programming and Data Science for Social Media — A quarter-long course taught by Tommy Guy that adapts and builds upon the CDSW curriculum to teach introductory programming and data science to absolute beginners in the context of the University of Washington's Communication Leadership program.
[Spring 2015] COM597: Programming and Data Science for Social Media — A quarter-long course taught by Benjamin Mako Hill that adapts and builds upon the CDSW curriculum to teach introductory programming and data science to absolute beginners in the context of the University of Washington's Communication Leadership program.

Resources

Based on the questions and requests we received from participants we compiled a list of resources available below:

Community Data Science Workshops (Winter 2020)/Resources

Wiki Best Practices

In order to make the process of creating future resources easier we compiled a list of best practices for editing the different types of pages on this wiki: Community Data Science Workshops (Winter 2020)/Wiki Best Practices