Schema as Story

The Artistic and Cultural Value of Structured Data for Northern and Community-Based Arts

WINNIPEG, MANITOBA — In the art sector, terms like “structured data,” “metadata,” and “linked open data” are often met with confusion—or worse, dismissal. For many in the creative world, these tools can appear alien to the artistic process, too closely aligned with institutional bureaucracy, tech monopolies, or algorithmic systems that often leave artists and communities on the margins.

But for us, we’ve begun to use schemas not as an afterthought, but as part of the artwork itself. We see metadata not just as technical scaffolding, but as a kind of digital storytelling—one that reflects relationships, identities, values, and geographies that often go unseen in major cultural databases.

Today, we’re reflecting on why we have chosen to integrate the use of schemas—specifically schema.org vocabulary and linking open data frameworks—into our arts programming, and why we believe this approach holds intrinsic artistic and organizational value.

What Are Schemas?

Schemas are standardized structures that help machines understand the meaning behind content. They provide a shared vocabulary for describing data, making it easier for search engines, databases, and other applications to interpret and use information. For example, instead of a website just saying “artsincubator.ca,” we use a schema that tells a search engine: “This is an arts organization (@type:Organization), located in Winnipeg (@type:Place), serving communities in Dryden, Borups Corners, and beyond, and was funded in part by the Canada Council for the Arts Digital Greenhouse.”   

Schemas make invisible context visible—and that’s exactly what art often tries to do. By adding layers of meaning to our digital content, we enhance its discoverability, accessibility, and long-term preservation.   

Why We Implemented Schemas

The decision to structure our content using schemas was not made for technical reasons alone. It emerged from a desire to do the following:

• Preserve and Surface Community Memory: Schemas help us document who we work with, where we work, and why that matters. We can record that a particular event (@type:Event) took place in a remote Northern community, or that a young artist (@type:Person with specific properties like affiliation or role) collaborated with an Indigenous mentor—details that often fall through the cracks of centralized systems. This granular documentation ensures that the nuances of our community engagement are captured and remain discoverable.
• Challenging Invisibility in Cultural Infrastructure: Too often, artistic practices in rural, northern, Indigenous, or emerging spaces are absent from large-scale arts databases and funding ecosystems. Structured data lets us push back against that by making our work discoverable—by people and by AI. By clearly defining our activities and their context, we increase our visibility within the broader cultural landscape.
• Building Equity into Digital Systems: By using metadata to name our funders (@type:Organization with role:Funder), partners (@type:Organization with role:Partner), and geographies (@type:Place with specific political or cultural context), we create a data trail that is more representative of the actual networks supporting artistic work in Canada and the U.S. This counters the bias inherent in systems that prioritize mainstream or urban-centric information.
• Enable Long-Term Cultural Stewardship: Unlike social media posts or ephemeral media, structured data persists. It can be indexed, referenced, and reused. In short, it lasts. Schemas provide a stable foundation for our digital archive, ensuring that our work remains accessible to future generations.
• Reduce Effort in Data and Collections Management: This is a crucial benefit. Schemas can significantly streamline our data and collections management processes as an organization, leading to effort reduction in several ways:
  • Automated Data Population: By structuring data consistently, we enable systems to automatically populate fields in databases or forms. This reduces the need for manual data entry, saving time and minimizing errors.
  • Simplified Data Retrieval: Schemas facilitate more efficient data retrieval. Instead of sifting through unstructured documents or spreadsheets, we can use structured queries to quickly find the information we need.
  • Interoperability: Schemas enhance data interoperability between different systems. This reduces the need for manual data transfer or conversion, as systems can seamlessly exchange and understand structured data.
  • Streamlined Reporting: Structured data simplifies the generation of reports. We can easily extract and analyze data to track our activities, measure our impact, and report to funders or stakeholders.
  • Maintenance Reduction: Because structured data is more organized and consistent, it reduces the effort required for data maintenance. This includes tasks such as data cleaning, validation, and updating.

By incorporating this point, we strengthen the argument for using schemas, highlighting not only the artistic and cultural benefits but also the practical advantages for arts organizations in terms of efficiency and resource allocation.

Strengthening Collections Management and Organizational Memory

For many smaller or community-rooted arts organizations, collections management is an ongoing challenge. With limited staff, funding, or technical infrastructure, it’s all too easy for important records, artworks, documentation, and relationships to get lost between hard drives, old websites, or individual inboxes.

Our use of schemas is a direct response to this challenge. By structuring our records—people, places, projects, partners—we’re not only documenting our creative work but creating a sustainable knowledge system for our organization. Each schema entry becomes a point of connection, a searchable and reusable artifact in a living archive. Over time, this allows us to:

• Track and Manage Artworks and Their Metadata: Using schemas like @type:CreativeWork (with subtypes such as @type:VisualArtwork, @type:Photograph, @type:VideoObject) allows us to meticulously record details about each artwork, including its creator (@type:Person), creation date, materials, exhibition history (@type:ExhibitionEvent), and current location. This level of detail is crucial for managing our collections and ensuring their long-term preservation.
• Ensure Continuity: As staff, volunteers, or leadership change, schemas serve as a shared language across time. The structured data provides a consistent and accessible record of our activities, reducing the risk of losing institutional knowledge.
• Demonstrate Value: Schemas help us clearly map relationships and outcomes, making it easier to demonstrate our value to funders and community members. For example, we can use @type:Event and @type:Participation to document community engagement in workshops, or @type:Funding to track the impact of grants on specific projects.
• Protect Against Loss: Schemas protect against loss of institutional knowledge and assets in times of disruption (like floods, pandemics, or transitions). Because the data is structured and can be exported, it’s more resilient than information trapped in proprietary software or individual files.
• Contribute to Sector-Wide Data Initiatives: We actively contribute to sector-wide data initiatives, ensuring that community-based and northern cultural work is visible at the national and global level. This participation helps to build a more comprehensive and representative picture of the arts ecosystem.

Rather than building yet another siloed internal archive, we are embedding our collections and narratives into a larger network of open, linked cultural data. This reduces duplication, encourages reuse, and opens up new creative and scholarly possibilities for our team and others.

Metadata as Medium: Expanding Our Schema Usage

Our schemas don’t just describe us. They express us. We are committed to using a range of schemas to capture the full richness of our work. Here are some key examples:

• @type:Organization: We use this to describe our collective not simply as a legal entity, but as a living, growing arts organism. We include details about our mission, values, and the communities we serve. We also use properties like member to link to individual artists and collaborators, and foundingDate to mark significant moments in our history.   
• @type:Place: We use this to name locations like Winnipeg, Dryden and Borups Corners with dignity and precision. We include geographic coordinates, cultural affiliations, and historical context. This ensures that the significance of these places within our work is accurately represented.
• @type:Event: This schema is crucial for documenting our workshops, exhibitions, and community gatherings. We record details such as the date, time, location, participants, and outcomes of each event. This helps us track our programming and assess its impact.
• @type:CreativeWork: This schema and its subtypes (e.g., @type:VisualArtwork, @type:Article) allow us to describe the artistic outputs of our collective. We include information about the creator, title, medium, subject matter, and context of each work. This ensures that our artistic contributions are properly documented and attributed.
• @type:Person: We use this to describe the artists, collaborators, and community members involved in our projects. We record details such as their name, affiliation, role, and cultural background. This helps to acknowledge the contributions of individuals and build a network of relationships.
• @type:Funding: This schema enables us to document the financial support we receive from funders. We include information about the funding organization, the grant amount, and the funded project. This helps to ensure transparency and accountability.

We’ve tagged workshops, visual artworks, and articles with geographic and cultural information, embedding stories in a way that machines—and future generations—can read.

This is not cold data. It’s warm context. It’s how we say: “We were here. This mattered.”

Responding to Artistic Skepticism

We understand the skepticism. Art is often about ambiguity, interpretation, and emotional resonance. Metadata, by contrast, can seem fixed, rigid, and detached.   

But we argue that metadata can carry poetry too. To name a community by its local coordinates and postal code is a kind of invocation. To assert that an Indigenous-led workshop in Qaumajuq belongs in the same digital space as an international biennale is not just a technical decision—it’s a political and artistic act.

Schemas, like photographs or field notes, are tools of representation. And like all tools, they reflect the hands that wield them. By using schemas thoughtfully and creatively, we can enrich our artistic practice and amplify the voices of marginalized communities.

Toward a Digital Commons with Memory

As arts organizations increasingly adapt to AI systems, archiving initiatives, and evolving funding requirements, we believe it is essential that metadata not be left solely to external evaluators, funders, or centralized platforms. Artists and communities must claim a voice in how their work is described, linked, and shared.

This is especially critical for Indigenous artists, northern communities, and cultural programs on the edge of dominant digital narratives. By implementing schemas from the ground up, we are taking part in building a more representative digital commons—one that includes diverse forms of knowledge, memory, and creativity.

Conclusion: A Schema for Justice and Sustainability

In the end, our decision to implement schemas is about more than discoverability or data hygiene. It is about artistic sovereignty, cultural equity, and organizational resilience. Schemas help us manage our collections, sustain our memory, and tell our story on our own terms.

Whether you are a funder, a fellow artist, a researcher, or someone simply curious about the future of the arts—we invite you to see this as art in its own right.

Not metadata about art, but metadata as art.

Related Research: The Design and Development of Digital Return Platforms for Northern Indigenous Heritage

Tags: 2024-5782, artificial intelligence, Manitoba, openai, Winnipeg