Community management guide#
These guidelines are applicable when acting as a representative of Matplotlib, for example at sprints or when giving official talks or tutorials, and in any community venue managed by Matplotlib.
Our approach to community engagement is foremost guided by our Mission Statement:
We demonstrate that we care about visualization as a practice
We deepen our practice and the community’s capacity to support users, facilitate exploration, produce high quality visualizations, and be understandable and extensible
We showcase advanced use of the library without adding maintenance burden to the documentation and recognize contributions that happen outside of the github workflow.
We use communications platforms to maintain relationships with contributors who may no longer be active on GitHub, build relationships with potential contributors, and connect with other projects and communities who use Matplotlib.
In prioritizing understandability and extensibility, we recognize that people using Matplotlib, in whatever capacity, are part of our community. Doing so empowers our community members to build community with each other, for example by creating educational resources, building third party tools, and building informal mentoring networks.
Official communication channels#
The Scientific Python community uses various communications platforms to stay updated on new features and projects, to contribute by telling us what is on their mind and suggest issues and bugs, and to showcase their use cases and the tools they have built.
The following venues are managed by Matplotlib maintainers and contributors:
library and docs: matplotlib/matplotlib
Mailing lists#
Maintenance#
If you are interested in moderating the chat or forum or accessing the social media accounts:
Matplotlib maintainers should reach out to the community-manager.
Everyone else should send an email to matplotlib-social-admin@numfocus.org:
Introduce yourself - github handle and participation in the community.
Describe the reason for wanting to moderate or contribute to social.
Content guidelines#
Communication on official channels, such as the Matplotlib homepage or on Matplotlib social accounts, should conform to the following standards. If you are unsure if content that you would like to post or share meets these guidelines, ask on the Social media coordination channels before posting.
General guidelines#
Focus on Matplotlib, 3rd party packages, and visualizations made with Matplotlib.
These are also acceptable topics:
Visualization best practices and libraries.
Projects and initiatives by NumFOCUS and Scientific Python.
How to contribute to open source projects.
Projects, such as scientific papers, that use Matplotlib.
No gratuitous disparaging of other visualization libraries and tools, but criticism is acceptable so long as it serves a constructive purpose.
Follow communication best practices:
Do not share non-expert visualizations when it could cause harm:
Clearly state when the visualization data/conclusions cannot be verified.
Do not rely on machine translations for sensitive visualization.
Verify sourcing of content (especially on instagram & blog):
Instagram/blog: ensure mpl has right to repost/share content
Make sure content is clearly cited:
e.g. a tutorial reworking an example must credit the original example
Limited self/corporate promotion is acceptable.
Should be no more than about a quarter of the content.
Visual media guidelines#
Visual media, such as images and videos, must not violate the code of conduct, nor any platform's rules. Specifically:
Visual media must conform to the guidelines of all sites it may be posted on:
Emphasize the visualization techniques demonstrated by the visual media.
Clearly state that sharing is not an endorsement of the content.
e.g. bitcoin related visualizations
Accessibility#
Visual media in communications should be made as accessible as possible:
Add alt text to images and videos when the platform allows:
Warn on bright, strobing, images & turn off autoplay if possible.
For images and videos made by the social media team:
Make graphic perceivable to people who cannot perceive color well due to color-blindness, low vision, or any other reason.
Do not make bright, strobing images.
More guidelines at https://webaim.org/techniques/images/.
Changing the guidelines#
As the person tasked with implementing these guidelines, the community-manager should be alerted to proposed changes. Similarly, specific platform guidelines (e.g. twitter, instagram) should be reviewed by the person responsible for that platform, when different from the community manager. If there is no consensus, decisions about guidelines revert to the community manager.
Social media#
Active social media#
https://twitter.com/matplotlib
https://instagram.com/matplotart/
Official accounts#
https://bsky.app/profile/matplotlib.bsky.social
https://fosstodon.org/@matplotlib
https://www.tiktok.com/@matplotart
https://www.youtube.com/matplotlib