Wikimedia LEADS: A Learning Ecosystem for the Wikimedia Movement

The Wikimedia Movement has always been more than a collection of websites. It is a global learning environment where people discover how to write, cite, translate, discuss, organize, document, photograph, model data, preserve knowledge, and collaborate across cultures. Yet much of that learning still happens informally: through trial and error, local mentoring, scattered documentation, project pages, workshops, edit-a-thons, and community memory. Many in the movement have identified this phenomenon as a very big handicap for newcomer onboarding. And we need to face it.

Wikimedia LEADS proposes a way to make the learning explicit, findable, reusable, and recognized.

Presented as a proposal for the Wikimedia Hackathon 2026 in Milano, Wikimedia LEADS imagines a shared learning infrastructure for the Wikimedia Movement. Its purpose is not to replace existing Wikimedia learning practices, but to support them through practices, competences, course contents, learning activities, learning evidence tracking and credentials in a learning ecosystem for the people.

First, the proposal responds to the internal challenge for newcomer onboarding: how can Wikimedians understand what they need to learn, find trustworthy guidance, demonstrate what they know, and make their skills discoverable to others?

Then, once we demonstrate that our learning ecosystem works, we can face the external challenge of how to stay relevant: extending it beyond the Wikimedia specifics to any other domain of human knowledge, launching a new project to build, share, and reuse learning artifacts as a new form of knowledge in and of itself.

The main outcomes will be:

• internally, a better Movement’s newcomer onboarding, capacity building, and knowledge management;
• externally, Wikimedia will continue staying relevant in a world where learning, credentials, digital trust, and knowledge infrastructures are an intrinsic need.

Wikimedia LEADS turns our internal necessity into an external opportunity.

Competences awareness challenge

For the contributor personal capacity building we identify these phases:

Where am I? Being new to Wikimedia can lead to feelings of insecurity when you realize there are many unspoken expectations that you feel you should know in order to contribute, but that you can’t quite pinpoint. There isn’t a simple guide you can consult and follow. At some point, this feeling can turn into disappointment and a sense of giving up. And this disappointment can happen to any of us: the Wikimedia Movement is so vast that any of us would be a beginner when trying a new activity.

I know what I don’t know. Now you have a map! Maybe you don’t know how to go from point A to B, but with a map you’ll be able to figure out how to do the trip. The same effect happens when you have a map of knowledge: now you can identify which skills you need to acquire to move from A to B, you can precisely identify what you ignore. This is more than Socrates could say!

I choose and develop my skills. You can identify which knowledge you have, your point A, and can identify and select the knowledge you need to acquire to get into point B, that is a learning path. Then, using the education resources available in the community and our learning software services, the learner can capacitate itself at their own pace.

Now I know, now I do. The learner has reached point B and can use its acquired skills in a new field. The newcomer moved from uncertainty to competence. It’s time to contribute.

Note that these phases are independent of the area of interest, like editing on a Wikipedia, dynamizing a local community, participating in public policies, developing software or whatever other one you could identify.

The proposed journey is intuitive:

• A contributor asks: Where am I?
• They become aware of what they know and what they do not know.
• They choose skills to develop.
• They learn through practice.
• They produce evidence through real Wikimedia activity.
• They earn verifiable credentials.
• They can then share those credentials so that others can discover their capacity.

Towards a learning ecosystem

We propose this approximation:

What is what?

Wikimedia practices: we adopt the SEMAT Essence concept of practice as «a way of work». This way we can model any Wikimedia real way of doing things (fact checking an article, patrolling a wikipedia, writing in Abstract Wikipedia…) using Essence as ontology over a Wikibase engine. We’ll see later more about Essence practices. Essence names a library to a set of practices. But also can be interpreted as a body of knowledge.

Course content: Just the usual content you can consume in the WikiLearn service.

Learning activity: The action of studying on a service like WikiLearn and passing a course and earning verifiable credentials.

Evidence: To pass a course you should show you have learned, collecting, as they say,  learning evidences. This evidences can be a passed test, a passed assignment and, for a Wikimedian, also a diff (or any other resource) successfully contributed. The learning evidences are linked in the earned credential, so can be used by a third party for checking your experience.

This is especially powerful because Wikimedia learning is not abstract. Contributors learn by doing: improving references, uploading media, translating articles, modeling Wikidata statements, documenting oral histories, organizing community events, patrolling edits, or teaching others. Wikimedia LEADS treats that activity as potential learning evidence.

Verifiable credentials: Have you heard about micro-credentials? Probably so. Verifiable credentials is a W3C for digital signed (micro-)credentials. And they are composed of Context, Issuer, Issue timestamp, Expiry timestamp, Type, Subject, Subject identity attributes and a Cryptographic proof. You can gather your earned credentials in a digital wallet and share at your convenience.

The architecture: connecting existing Wikimedia services

One of the strengths of the proposal is that it builds on the existing Wikimedia services and community ecosystem.

• The Wikimedia Movement Body of Knowledge would describe practices, competences, and credential definitions. This becomes the formal conceptual map of what Wikimedians know and do.
• Wikiversity could host or connect course content.
• Learn.wiki can provide course delivery and assessment.
• Sister projects can provide real user contributions that function as learning evidence.
• Outreach Dashboard can track activity and aggregate learning records.
• A Wikimedia learner backpack can store standard verifiable credentials.
• Capacity Exchange can use those credentials to help people find one another by skills and capacities.

This is not merely a training platform. It is a bridge between knowledge, practice, evidence, recognition, and collaboration.

From an engineering point in view can be described like this:

Practices, competences, credentials, and learning paths

The information model behind Wikimedia LEADS is deliberately simple:

• A practice is a reusable Wikimedia way of working: for example, assessing whether a source is trustworthy before using it as a reference.
• A competence describes what a learner can do.
• A credential is a recognized unit of learning.
• A verifiable credential is a cryptographically verifiable certificate that can be stored and shared.
• A learning path is a credential that stacks several other credentials, effectively working as a curriculum.

This structure matters because it allows Wikimedia knowledge to be broken into reusable, connected units. A single practice can require competences. A course can support credentials. A credential can certify a competence. Several microcredentials can be stacked into a learning path. A learning path can guide a newcomer, a campaign organizer, a GLAM contributor, or a technical volunteer through a coherent sequence of learning.

From an engineering point in view can be described like this:

Three user stories

Here we propose three example stories that show how this ecosystem would work in practice.

In the first story, a Wikimedian wants to know how to review the trustworthiness of a source before using it as a reference. They use the Body of Knowledge Explorer to find the relevant practice, read the guidance, and apply it in their Wikimedia work.

In the second story, another contributor explores the same topic but discovers that there are credentials related to knowledge they already have. They enroll in a course, earn verifiable credentials, and publish them in Capacity Exchange so others can find them by their skills.

In the third story, a recent Wikimedian is asked to improve references. They explore the Body of Knowledge, identify the required skills, enroll in a course, and learn while fixing real edits. Those edits become learning evidence. The contributor earns verifiable credentials and saves them in a personal backpack.

BoK Explorer: a knowledge interface for Wikimedians

To best illustrate the power of our proposal here is an AI generated mockup of what could be full featured an end-user interface to explore a practice about how assess references trustworthiness:

A more light interface, for the same example:

And, to show how the same technology can be applied to a completely different domain, this is how a practice of nitrogen cooking could look:

I don’t know your opinion, but for us this look awesome.

Alignment with Wikimedia 2030

Wikimedia LEADS is also framed as a contribution to the Wikimedia Movement Strategy 2030.

It directly supports recommendations such as:

• Invest in Skills and Leadership Development
  The ecosystem makes learning paths, competences, and credentials explicit.
• Manage Internal Knowledge
  The Body of Knowledge becomes a structured map of Wikimedia practices.
• Innovate in Free Knowledge
  The project experiments with verifiable credentials, learning evidence, and reusable knowledge models.
• Coordinate Across Stakeholders
  Credentials and capacity profiles can help communities, affiliates, projects, and partners find people with relevant skills.

It also contributes to:

• Improve User Experience 
• and Increase the Sustainability of Our Movement.

Contribution to the Wikimedia Futures Lab goals

LEADS supports movement belonging through better onboarding and systematic capacity building. It responds to global trends such as microcredentials, lifelong learning, and emerging skills data spaces. And it proposes a concrete strategy for keeping Wikimedia relevant in a changing knowledge environment.

Why LEADS matters

Wikimedia is one of the most successful learning communities in the world, but it does not always recognize itself as one.

Every day, contributors acquire complex skills: source evaluation, copyright reasoning, metadata modeling, community facilitation, multilingual communication, data curation, conflict resolution, software development, archival description, and more. These skills are valuable inside the Movement and beyond it.

Wikimedia LEADS proposes that these skills should be easier to discover, learn, practice, evidence, and recognize.

That recognition does not need to be bureaucratic. It can be open, portable, standards-based, and rooted in real contribution. A contributor’s work on Wikimedia projects can become part of their learning journey. A credential can point back to evidence. A learning path can guide future contributors. A capacity exchange can help communities find the people they need.

From learning to leadership

The most promising aspect of Wikimedia LEADS is that it treats learning as infrastructure.

• Not as an isolated course catalog.
• Not as a one-time newcomer tutorial.
• Not as a badge system disconnected from practice.

Instead, it imagines a movement-wide learning ecosystem where knowledge, action, evidence, and recognition reinforce one another.

For newcomers, this could mean clearer onboarding.

For experienced contributors, it could mean recognition and visibility.

For affiliates and communities, it could mean better capacity mapping.

For the Wikimedia Movement as a whole, it could mean a stronger foundation for skills development, internal knowledge management, and long-term relevance.

Wikimedia LEADS offers one possible path toward that future: a learning ecosystem where Wikimedians can find what they need to know, learn by doing, prove what they can do, and help others grow. An ecosystem to be the foundation of open learning for the world. Let’s build the future.

Acknowledgments

Thanks to Wikimedia España for sponsoring my participation in the Hackathon through the Wikipedia donors funds they manage.