Entityis

Entityis is a hypothetical framework and data standard designed to describe, identify, and interoperate discrete entities within digital knowledge graphs. It provides a formal data model for entities, their identifiers, attributes, relationships, and provenance, with emphasis on stable identity across systems and over time.

The core concepts of entityis include persistent identifiers, human-readable labels, typed properties, and relational edges that link entities into graphs. Each entity is assigned an entityis ID, which remains stable even as properties evolve. The model supports disambiguation gates and alternate representations to handle synonymy and homonymy.

Architecturally, entityis envisions a layered stack: a core entity model, a mapping layer to convert between existing standards (such as RDF/OWL or JSON-LD), a validation layer for schema compliance, and a query/interface layer enabling discovery through graph queries. Serialization formats commonly referenced include JSON-LD-like structures and compact binary encodings for efficiency.

Interoperability is a central goal; entityis is designed to align with established knowledge-graph practices, promote reuse of common entity templates, and enable cross-system identity reconciliation. Critics note that as a hypothetical concept it lacks formal governance, which could hinder adoption and create fragmentation if realized.

Example: an entity representing a scientist might have an id, a preferred label, birth year, and links to published works, while a separate person-entity could be linked via a "co-authored" relation. This simple depiction illustrates how entityis aims to support stable identity and rich context in distributed data.