Coko is an open source platform that connects cultural heritage institutions, developers, and creative communities. It enables rich digital collections to be described, linked, and reused across websites, apps, and research projects.
By combining linked data, open standards, and extensible APIs, Coko supports museums, galleries, and archives in publishing interoperable knowledge graphs. The following sections outline key product areas, technical choices, and practical guidance.
| Product | Primary Use | Key Standard | Typical Integration |
|---|---|---|---|
| Coko Platform | Digital asset and metadata integration | Linked Data, JSON-LD | Websites, research portals |
| Coko Harvester | Batch ingestion from source systems | OAI-PMH, HTTP, S3 | Archival pipelines, exports |
| Coko Flow | Orchestration and transformation | RDF, CSV, XML mapping | ETL workflows, data cleaning |
| Coko Connector | Third-party system integration | REST, GraphQL, Webhooks | CMS, CRM, digital repositories |
Core Data Modeling Capabilities
Entity Relationships and Schemas
Coko emphasizes semantic modeling with rich entity relationships such as people, organizations, events, and places. Schemas are expressed using vocabularies like CIDOC CRM, ensuring long-term semantic interoperability across collections.
Designers can define classes, properties, and constraints through visual editors or configuration files. This approach keeps metadata expressive yet manageable, supporting both human curators and automated pipelines.
Ingestion and Harvesting Workflows
Batch and Realtime Data Capture
The Harvester module supports scheduled batch pulls as well as event-driven updates. It normalizes incoming records into a canonical model, reducing duplication and aligning variant descriptions from different departments.
Robust logging and retry mechanisms help operations teams monitor health and recover from partial failures. Detailed audit trails clarify how each item entered the system and when changes occurred.
Transformation and Enrichment
Mapping, Validation, and Enrichment
Coko Flow provides visual mapping tools to align source fields to target schemas. Rules can normalize dates, expand abbreviations, and enrich records with external references such as Wikidata or Getty vocabularies.
Built-in validation flags inconsistencies before data is published, allowing curators to review proposed edits. Versioned transformation pipelines make it straightforward to iterate on mappings as standards evolve.
Publishing and Interoperability
Linked Open Data and API Exposure
Published datasets are exposed as Linked Open Data with stable URIs, enabling other systems to link across collections. JSON-LD and RDF serialization support modern semantic web applications and knowledge graph integrations.
GraphQL and REST APIs offer flexible access patterns for developers. Fine-grained permissions ensure that sensitive or restricted materials are only visible to authorized users while still supporting open discovery.
Operational Best Practices and Recommendations
- Define clear entity models and URI strategies before bulk ingestion.
- Use transformation pipelines to normalize dates, names, and geographic references.
- Implement staged publishing with review environments for metadata changes.
- Monitor harvest jobs and set alerts for failed runs or schema drift.
- Leverage linked data exports to connect your collections with external datasets.
FAQ
Reader questions
How does Coko handle version control and change tracking?
Coko records each transformation step and metadata change with timestamps and operator identifiers, enabling detailed lineage views and reversible edits where needed.
Can Coko integrate with existing museum collection management systems?
Yes, connectors for common TMS and DAM platforms allow bidirectional sync or one-way harvesting, depending on institutional workflows.
What licensing and community support options are available?
Coko is open source with an active community, offering both community support channels and commercial support options for mission-critical deployments.
How scalable is Coko for very large digital libraries?
Designed for horizontal scaling, Coko can process millions of records through distributed harvesting and transformation jobs.