piramideschemas

Piramideschemas is a term used to describe a class of data schemas organized in a hierarchical, pyramid-like structure to model information at multiple levels of abstraction. In this model, the base layer captures broad, raw data entities and basic attributes, while successive upper layers introduce increasingly integrated, context-rich schemas, culminating in a top layer that expresses domain-specific concepts and ontologies. The approach emphasizes aggregation, inheritance, and containment relationships to enable scalable querying and governance across large datasets.

Although not universally standardized, the term has appeared in discussions of data architecture and knowledge management to contrast flat schemas with multi-level hierarchies. It is often presented as a middle ground between relational models and fully formal ontologies, offering structured guidance for organizing data while preserving flexibility in representation and evolution.

Core characteristics include explicit layering that separates raw data from integrated concepts, support for schema derivation and inheritance, and compatibility with multiple data representations such as relational, JSON-based documents, or graph structures. Piramideschemas typically support versioning and lineage tracking to document how each layer is derived and how changes propagate upward through the pyramid. The approach favors clear boundaries between levels while enabling cross-layer queries and aggregation.

Applications include data governance, business intelligence, analytics, and knowledge graphs, where hierarchical schemas help manage scope, access, and interpretation of data across departments. Limitations involve complexity in design and maintenance, potential performance trade-offs for cross-layer queries, and the risk of overfitting a pyramid model to domains where flat or ontological representations may be more appropriate.