• Website: https://jupytercon.com/
• Location: Online
• Date: 5-9 October 2020

• Subtitle: Open Source Fundamentalis
• Duration: 2h (120 minutes)
• Audience level: Anyone interested in learning about Open Source communities
• Prerequisite: None

Short Description:

This tutorial is a part of the Jupyter 2020 series on Open Source Fundamentals. It is organised in 4 short modules that are developed in Jupyter Notebooks and paired with introductory videos.

1. Diversity, Inclusion, Inclusiveness: 1-diversity-inclusion-inclusiveness.ipynb
2. Communities of Practice: 2-community-of-practice.ipynb
3. Community Collaboration: 3-community-collaboration.ipynb
4. Decision-Making Processes: TBA

Please visit the notebooks directory to find the tutorial files (named module-wise). All the presentations used in the introductory videos are provided in the presentation directory.

Session detail:

The tutorial will introduce our learners to basic concepts and practices necessary to build diverse and inclusive Open Source communities.

• In the first module, we will discuss how both system and actions that are important to design and promote inclusiveness Open Source projects
• In the second module, we will introduce what Communities of Practice are, give examples from Open Source, discuss how we can support its diverse members and explain how we can move "from default to inclusive practices" in Open Source
• The third module builds on the first and second modules and discusses collaborations in Open community, pathways for engagement with the contributors and resources that make these collaborations secure, effective and community-oriented
• Finally, in the last module, we learn about decision-making processes in the Open Source communities by explaining contributor roles, structure and leadership of Open Source communities, and ways to recognise volunteers of Open Source community

In this tutorial, our learners will:

• understand the roles of diversity and inclusion of open source communities
• learn about the concept of Community of Practice, how they look like in different Open Source communities, who the members of these communities are and how we can design projects for participation
• explore collaborative roles of community members, platforms that facilitate their contributions to a project, channels to attract new contributors and resources that set a common norm in the community
• understanding the leadership structure of Open Source, what roles contributors play in the project development processes and how volunteers can be fairly recognised for their work

• Name: Malvika Sharan

  • Title: Dr.
  • Organization: The Turing Way, The Alan Turing Institute, London, UK
  • Biography: Malvika is the community manager of The Turing Way at The Alan Turing Institute, UK. She works with its community of diverse members to develop resources and ways that can make data science accessible for a wider audience. Malvika has a PhD in Bioinformatics and she worked at European Molecular Biology Laboratory, Germany, that helped her solidify her values as an Open Researcher and community builder. She is a co-founder of the Open Life Science mentoring program, a fellow of the Software Sustainability Institute and a board member of Open Bioinformatics Foundation, where she focuses on training resources and fellowship programs to enhance the training, skill building and representation of marginalised groups in data science and bioinformatics.
  • Photo: LINK

• Name: Gabriela de Queiroz

  • Title: Sr. Engineering & Data Science Manager
  • Organization: IBM, California
  • Biography: Gabriela de Queiroz is a Sr. Engineering & Data Science Manager at IBM where she manages and leads a team of developers working on Data & AI Open Source projects. She works to democratize AI by building tools and launching new open source projects. She is passionate about making data science available to everybody and is actively involved with several organizations to foster an inclusive community. She is the founder of AI Inclusive, a global organization that is helping increase the representation and participation of gender minorities in Artificial Intelligence. She is also the founder of R-Ladies, a worldwide organization for promoting diversity in the R community with more than 180 chapters in 50+ countries. She has worked in several startups where she built teams, developed statistical models and employed a variety of techniques to derive insights and drive data-centric decisions.
  • Photo: LINK