Hocquerying

Hocquerying is a paradigm for formulating queries over data sources that support higher-order constructs. It extends conventional query languages by treating predicates, relations, and even entire queries as first-class objects that can be passed as arguments, returned as results, or composed to form new queries. In practice, hocquerying enables meta-queries, relational composition, and context-sensitive retrieval, allowing users to express queries about the structure of data as well as the data itself.

Origin and terminology: The name combines 'hoc' for higher-order context or higher-order components with querying. The concept draws on higher-order logic, type theory, and semantics of knowledge graphs. In literature, hocquerying is described as a capability of advanced query systems to manipulate not only data items, but the queries themselves.

Core concepts: Higher-order predicates—where relations themselves can be quantified or transformed; query combinators—operators that map, filter, or compose queries; and context-aware constraints—that propagate conditions across related entities. Safety and decidability are central concerns, leading to restricted fragments or typed formats that guarantee termination or tractability in practical systems.

Implementation approaches vary. Some systems extend SQL-like languages with higher-order features; others embed hocquerying in logic programming or functional paradigms. Graph databases and knowledge graphs may provide higher-order capabilities through query operators, meta-queries, or programmable connectors.

Applications include semantic search, data integration, and scientific literature analysis, where the ability to reason about relations between relations enables richer retrieval patterns. Researchers explore optimization and usability to mitigate complexity and performance costs inherent to higher-order querying.

See also: higher-order logic, meta-queries, knowledge graphs, query rewriting, typed lambda calculus.