occurare

Occurare is a theoretical framework and, in some depictions, a software platform for modeling and analyzing occurrences of events within texts, data streams, and datasets. It treats an occurrence as a concrete instantiation of an event, marked by a time, place, and participants, allowing precise temporal localization and cross-source alignment. The term is used in speculative and academic contexts to illustrate how event data can be structured and queried.

Etymology: The name combines occur- from Latin occurre (to meet, happen) with -are, a common suffix in neologisms, underscoring its focus on occurrences rather than the events themselves.

Core concepts and architecture: At its core, Occurare differentiates between events (types) and occurrences (instances). Primary entities include events, occurrences, actors, timestamps, and contexts. A typical implementation envisions a modular stack with ingestion (extracting occurrences from text or streams), a storage model (graph- or time-indexed), a query engine oriented to temporal and relational constraints, and visualization or analytics components.

Applications: In digital humanities, Occurare supports cross-source alignment of historical events. In journalism and compliance, it helps track reported incidents and policy violations. Researchers use it to study narrative structures and temporal patterns across corpora.

History and reception: The concept emerged in speculative literature and early academic proposals in the 2010s as a means to address temporal localization and provenance in event data. While popular as a design idea, concrete implementations remain limited to experimental tools or hypothetical models, cited for emphasizing provenance, reproducibility, and temporal locality.

See also: Event extraction, temporal databases, knowledge graph, narrative reasoning, data provenance.