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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 extensiblity, 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:

Social media#

Active social media#

Official accounts#

Mailing lists#

Social media coordination#

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:

  • 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:

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/.

Social media#

Matplotlib aims for a single voice across all social media platforms to build and maintain a consistent brand identity for Matplotlib as an organization. This depersonalization is the norm on social media platforms because it enables constructive and productive conversations; People generally feel more comfortable giving negative and constructive feedback to a brand than to specific contributors.

The current Matplotlib voice and persona aims to be kind, patient, supportive and educational. This is so that it can de-escalate tensions and facilitate constructive conversations; being perceived as negative or argumentative can escalate very fast into long-lasting brand damage, being perceived as personal leads to aggression and accusations faster than an impersonal account, and being perceived as friendly and approachable leads to higher engagement. Instead of speaking with a directive authority, which can be intimidating and lead to negative engagement, it speaks as a peer or educator to empower participation. The current voice encourages more input from folks we engage with, and also makes it possible for folks who are not in the core team to participate in managing the account.

While the brand identity is casual, the showcased content is high quality, peer-led resource building. Please follow these guidelines to maintain a consistent brand identity across platforms.

Persona#

On social media, Matplotlib:

  • Acts as a sentient visualization library, so talks about itself as a we, us, our, and it. Avoids talking about itself in the 3rd person. Never uses 1st person.

  • Is very earnest, eager to please, and aims to be patient & painfully oblivious to snark and sarcasm.

  • Gets over-excited over shiny visualizations - lots of emojis and the like - and encourages folks to share their work.

  • Highlights various parts of the library, especially the more obscure bits and bobbles.

  • Acknowledges that it is a sometimes frustrating tangle of bits & bobbles that can confuse even the folks who work on it & signal boosts their confuzzlment.

Behavior#

When acting as a representative of the library, keep responses polite and assume user statements are in good faith unless they violate the code of conduct.

Social graph#

Only follow organizations and projects, do not follow individual accounts for any reason, even maintainers/project leads/famous Python people!

Following these types of accounts is encouraged:

  • NumFocus and Scientific Python projects

  • 3rd party packages

  • Visualization related projects and organizations

  • Open Source community projects

  • Sponsors

Recurring campaigns#

Typically the social media accounts will promote the following:

  • Matplotlib releases:

    • Highlight new features & major deprecations

    • Link to download/install instructions

    • Ask folks to try it out.

  • third party packages

  • NumFocus/Scientific Python/open source visualization project releases

  • GSOC/GSOD recruiting and progress

Retired campaigns#

  • John Hunter Excellence in Plotting, submission and winners

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.

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