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A Guide to Hosting Your Project in LF AI & Data

By October 10, 2019November 6th, 2024No Comments

Building an open source software project and wanting to gain traction? Just providing a software repo, mailing list, and a website is not enough. A much wider set of services, including scalable and neutral governance, is critical for increasing adoption of open source projects.

The LF AI & Data Foundation provides a wide range of services for its hosted projects with a focus on increasing development and innovation in the open source AI ecosystem. By being part of LF AI & Data, a hosted project gets access to program management services, event management services, marketing services and programs, PR support, legal services, and staff eager to help grow your project.

All services act as enablers to propel your project further, providing solid ground on which various organizations and interested individuals would feel propelled to join the project and be part of its community of users and/or contributors versus other projects.

Why host a project under LF AI & Data?

  1. You believe your project will gain wider community adoption if it’s no longer solely affiliated with a corporate partner
  2. Several companies are working on very similar projects, and transferring management to an open source foundation would unite people under a common project
  3. There are legal or administrative tasks essential to the health of your project, and it’s not clear which current participant should own these tasks. These types of needs typically only arise after a project has already become reasonably established, with an active contributor community and often one or more dedicated corporate partners.

How are projects on-boarded into LF AI & Data?

Projects are on-boarded and progress pursuant to the LF AI & Data Foundation’s Project Process and Lifecycle Document.

LF AI hosted projects fall into one of three stages: Sandbox, Incubation, and Graduated

Sandbox Incubation Graduated

The core 5 requirements for a project to qualify as a sandbox project are:

1. Use an approved OSI open source license

2. Be supported by an LF AI and Data member

3. Fit within the mission and scope of LF AI and Data

4. Allow neutral ownership of project assets such as a trademark, domain or GitHub account (the community can define rules and manage them)

5. Have a neutral governance that allows anyone to participate in the technical community, whether or not a financial member or supporter of the project

To graduate, the project must receive the affirmative vote of the TAC.

In addition to the incubation requirements, a project must meet these requirements:

1. Have a healthy number of committers from at least two organizations

2. Have achieved and maintained a Core Infrastructure Initiative Best Practices Badge

3. Demonstrate a substantial and ongoing flow of commits and merged contributions

4.Document current project owners, and current and emeritus committers in OWNERS.md and COMMITTERS.md files

5. Document project’s governance (we help projects create a governance model that works for them or simply help them document their existing governance).

To graduate, the project must receive the affirmative vote of the TAC.

To be accepted into the Graduation stage, a project must meet the Incubation stage requirements plus:

1. Have a healthy number of code contributions from at least 5 organizations.

2. Have reached a minimum of 1000 stars on Github.

3. Have achieved and maintain an OpenSSF Best Practices Program (Gold)

4. Have completed at least one collaboration with another LF AI & Data project.

Since some of these criteria can vary depending on a project’s type, scope, and size, the TAC has final judgment over the activity level adequate to meet these criteria. 

To graduate, the project must receive the affirmative vote of the TAC and the Governing Board.

When a project graduates, it will be eligible to have a technical lead appointed to represent the project on the LF AI & Data Technical Advisory Council. The project is expected to nominate a lead to the TAC who can attend and participate in the bi-weekly TAC calls..
Accepting sandbox projects into LF AI requires a positive vote of the Technical Advisory Council (TAC) Accepting incubation projects into LF AI requires the positive vote of both the TAC and the Governing Board Accepting graduation projects into LF AI requires the positive vote of both the TAC and the Governing Board

How does Your Project Transition from Incubation to Graduation?

The TAC undertakes an annual review of all LF AI hosted projects to assess whether each Incubation stage project is making adequate progress towards the Graduation stage, and whether each Graduation stage project is maintaining progress to remain at Graduation level.

The TAC then provides a set of recommendations for each project to improve and/or a recommendation to the LF AI Governing Board on moving a project across stages.

Common Benefits to Incubation and Graduation Projects

  • Access to a larger community within that same ecosystem leading to larger pipeline of potential users and contributors
  • Validation from the Linux Foundation, trusted source that hosts over 180 large scale open source projects
  • Scalable and neutral governance accessible to all
  • Neutral hosting of your project’s trademark and any related assets and accounts
  • Marketing and awareness
  • Collaboration opportunities with other LF AI projects and broadly other Linux Foundation projects
  • Compliance scans with reports delivered to the projects’ mailing lists
  • Infrastructure and IT enablement (specifics depend on each project and the hosting level)

Specific Benefits for Incubation Projects

In addition to the above stated common benefits, Incubation projects enjoy these additional benefits:

  • Your project has the right to refer to the project as an “LF AI Foundation Incubation Project”
  • Appointment of an existing TAC member that will act as a sponsor of your project and provide recommendations regarding governance best practices
  • Access to LF AI booth space at various events for demo purposes  and for meeting the developer community, based on availability

Specific Benefits for Graduation Projects

In addition to the above stated common benefits, Graduation projects enjoy these additional benefits:

  • Your project has the right to refer to itself as an “LF AI Graduation Project,” which signals to the market that your project has reached a high level of technical maturity with confidence in its readiness for deployment
  • Projects designed as Graduation Projects by the Governing Board get a voting seat on the TAC
  • Graduation projects are eligible to request and receive funding support contingent on Governing Board approval
  • Priority access to LF AI booth space at various events for demo purposes and for meeting the developer community
  • Graduation projects have a technical lead appointed for representation of your project on the TAC

Join LF AI & Data as a Project

We’re constantly looking for new projects to join our family. Please reach out to info@lfai.foundation if you’d like to discuss the prospect of your open source AI project joining LF AI & Data as a hosted project.

LF AI & Data Resources

 

Author

  • Andrew Bringaze

    Andrew Bringaze is the senior developer for The Linux Foundation. With over 10 years of experience his focus is on open source code, WordPress, React, and site security.

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