Getting the Most Out of Working Groups

css.php
Getting the Most Out of Working Groups

An important pillar of the ethos of the GCDI community is collective, collaborative inquiry. With this in mind, the GC Digital Fellows lead a number of different working groups that nurture interdisciplinary conversations, learning, and feedback. Building these kinds of communities of practice is especially important at a time when the COVID-19 pandemic has limited those prized serendipitous encounters that are a valued part of graduate school life. 

If you’re unfamiliar with our working groups, the following post includes a quick introduction to those supported by GC Digital Initiatives and a few pointers about how to get involved in order to take advantage of what these groups have to offer.

What is a working group? 

  • A loosely organized and informal collective 
  • Focuses on an interdisciplinary technology topic
  • Welcomes novice to expert users
  • A place to share your work and get feedback, to ask and answer questions
  • Holds occasional meetings (attendance is never required) 
  • Makes use of a Group forum on the Commons (and, occasionally, other platforms as well)

How do I participate? 

Why do I want to join a working group? 

  • To join a community of scholars working along and across methodological and disciplinary lines 
  • To learn by doing
  • To problem-solve collaboratively 
  • To share and build resources 
  • To begin or join conversations on methodological and theoretical concerns 

If you are interested in participating in any of the specialized communities of interest to learn together, make connections, or share your work, feel free to join their group on the CUNY Academic Commons! 

The GIS/Mapping Working Group is a network of CUNY students, faculty and staff interested in sharing methods and techniques, and finding support from others about ways GIS can be used to further research and teaching. It offers a discussion space and a forum where students, faculty, and staff can present their projects. 

The Python User’s Group (PUG) is an open and informal collaborative space for experimentation and exploration with the Python programming language, where all interested in Python – from complete beginners to advanced users – can come to work together and find support for their projects, learn skills, tools, or just hang around. Similarly, the R User’s Group (RUG) is a place for newbies and experts alike to learn and work together on projects using the statistical programming language, R. Whether you’re looking to learn a new library, or to solve a challenge collectively, PUG and RUG are the spaces you are looking for. 

The Digital Archives Research Collective (DARC) is a platform that aims to address the needs of students, faculty, and communities working on archival research at The Graduate Center. Its primary goal is to assist in the creation of digital archives and exhibitions, but DARC also provides resources (in the form of tutorials, best practices, and workshops) on the archival research process itself and the theoretical concerns around archival work.

The Sound Studies and Methods Working Group is a network of CUNY students, faculty, and staff interested in sharing theories, methods, and techniques related to doing qualitative and quantitative research, teaching, storytelling, and creating art with sounds and audio files, and finding resources and support from others to do so. The group is open to scholars from all disciplines to explore ways that we as researchers and makers can study and use sound in our scholarship and pedagogy. If you’re working on a podcast for your class or your research project, you might want to join the Sound Studies and Methods Working Group. 

The Data Visualization Group (DVG) is a newly born working group where folks interested in sharing theories, methods, and techniques related to data visualization can come and ask questions on their projects or learn new tricks. Members are encouraged to meet to discuss topics such as data preprocessing, data explanation, data exploration, theories of data visualization, real-world examples, and ongoing work. Throughout the academic year, DVG will explore the fundamentals of data visualization including design principles, best practices, dashboards, visualization tools, ethics, and more. 

Can’t find the community you were looking for? Check out the Participate page on the GCDI website! If a group matching your interests doesn’t exist yet, create it yourself using the CUNY Academic Commons! 

Stefano Morello is a doctoral candidate in English with a certificate in American Studies at The Graduate Center, CUNY and a Teaching Fellow at Queens College, CUNY. His academic interests include American Studies, pop culture, poetics, and digital humanities. His dissertation, “Let’s Make a Scene! East Bay Punk and Subcultural Worlding,” explores the heterotopic space of the East Bay punk scene, its modes of resistance and (dis-)association, and the clashes between its politics and aesthetics. He serves as co-chair of the Graduate Forum of the Italian Association for American Studies (AISNA) and is a founding editor of its journal, JAm It! (Journal of American Studies in Italy). As a digital humanist, Stefano focuses on archival practices with a knack for archival pedagogy and public-facing initiatives. He created the East Bay Punk Digital Archive, an open access archive of East Bay punk-zines, and worked as a curator and consultant for Lawrence Livermore’s archive at Cornell University. He was a Wellcome Trust Transdisciplinary Fellow in 2019-2020.

0 Comments

Leave a reply

Your email address will not be published. Required fields are marked *

*

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Need help with the Commons? Visit our
help page
Send us a message
Skip to toolbar
https://digitalfellows.commons.gc.cuny.edu/2020/12/08/getting-the-most-out-of-working-groups/?utm_source=rss&utm_medium=rss&utm_campaign=getting-the-most-out-of-working-groups
digitalfellows.commons.gc.cuny.edu
crawl=CC-MAIN-2021-04
126347
application/http; msgtype=response
sha1:W3XRCWT6K6PTRRCAZ4FAYVUHLDXSOGZ5
<urn:uuid:5596e6b2-fca3-45c2-9f0e-02d3304a03f4>
2021-01-22T04:49:49Z
146.96.128.200
text/html
sha1:QYVTA5GO6XXP4PPCAQ4FTERMBYNBQWH7
<urn:uuid:c7385017-01cf-4db1-b010-17f0b0aff55f>
https://digitalfellows.commons.gc.cuny.edu/2020/12/08/getting-the-most-out-of-working-groups/?utm_source=rss&utm_medium=rss&utm_campaign=getting-the-most-out-of-working-groups
response
<urn:uuid:d72b79cc-7375-4823-a660-956aafd9091e>
isPartOf: CC-MAIN-2021-04
publisher: Common Crawl
description: Wide crawl of the web for January 2021
operator: Common Crawl Admin (info@commoncrawl.org)
hostname: ip-10-67-67-103.ec2.internal
software: Apache Nutch 1.17 (modified, https://github.com/commoncrawl/nutch/)
robots: checked via crawler-commons 1.2-SNAPSHOT (https://github.com/crawler-commons/crawler-commons)
format: WARC File Format 1.1
conformsTo: http://iipc.github.io/warc-specifications/specifications/warc-format/warc-1.1/