Data Architecture Documentation
Document data architecture with a model-first workflow: define entities in the central model, then create ERD views, graph views, search views, schemas, and API definitions as derived representations.
Content Foundry takes a model-first approach to data architecture documentation. The central data model (model.neoarc) defines all entities, properties, relationships, and constraints once. Multiple views, schemas, and API definitions derive their data from this single source of truth, keeping consistency across every representation.
Model-First Workflow
The model-first workflow begins with the central model and produces derived artefacts for different audiences and use cases.
Data Architecture Artefacts
The following artefact types support data architecture documentation in NeoArc Studio.
The Central Model as Starting Point
The central model (model.neoarc) is a GraphDocument with isProjectModel: true and authoringMode: "graph-db". It stores entities as nodes and relationships as edges, with full support for properties, key roles, constraints, governance metadata, and multi-domain projections (persistence, search, API).
| Model Feature | Description |
|---|---|
| Entities (nodes) | Domain concepts with labels, properties, and governance metadata |
| Relationships (edges) | Typed connections with cardinality, labels, and edge properties |
| Groups | Logical subdomains that organise entities (e.g. Customers, Orders, Products) |
| Abstract types | 12 database-agnostic property types that map to concrete types via profiles |
| Key roles | 6 key role types: primary, foreign, natural, surrogate, composite-part, none |
| Projections | Per-property configuration for persistence, search, API, and custom contexts |
| Governance | Data classification, retention policies, compliance notes, encryption flags |
| Composite constraints | Multi-property index and uniqueness constraints |
| Validation | 18 validation rules across structural, semantic, and domain categories |
View Types for Data Architecture
Data Warehouse Schemas
Star and snowflake schemas for analytics use cases are modelled in the central model with appropriate entity groups and relationships. Create ERD views to visualise fact and dimension tables with the target database profile applied.
Data Flow and Lineage
For data flow diagrams and data lineage documentation, use the standard diagram editor with data flow shapes, containers, and labelled connections. These diagrams complement the model-first views by showing how data moves between systems, rather than the static structure of entities.
Getting Started
Explore the guides in this section.