connectrelate

ConnectRelate is a conceptual framework and family of methods for connecting and relating data from multiple, diverse sources through structured modeling of entities and their relationships. It emphasizes graph-based representations in which objects such as people, organizations, events, and products are modeled as nodes and the connections between them as edges.

Key components include data connectors to ingest diverse sources, an identity resolution module to unify records that refer to the same real-world entity, a relationship inference engine to propose and encode connections that are not explicit, and a provenance and governance layer to track origins, confidence, and privacy constraints. A flexible ontology or schema enables modeling of heterogeneous domains.

Operational principles often involve schema-agnostic ingestion, deduplication, probabilistic or rule-based matching, and graph-based querying and traversal. The approach supports incremental updates, scalability, and conflict resolution, while emphasizing data provenance and access controls.

Common use cases include consolidating customer data across CRM, ERP, and marketing platforms; linking authors, publications, and funding in research ecosystems; detecting fraud or risk through interconnected signals; and enabling knowledge graphs for enterprise search and analytics.

In scholarly and industry literature, connectrelate is described as a methodological approach rather than a single product, with implementations ranging from custom graph pipelines to components integrated into graph databases and data integration platforms.

Related concepts include entity resolution, data linkage, graph databases, and knowledge graphs.