sam∗: A semantic association model for corporate and scientific-statistical databases☆

摘要: Abstract This paper describes a semantic Association Model called sam ∗ which is designed for modeling not only scientific-statistical databases but also business-oriented databases. The model uses “concepts” and “associations” of these concepts to the real-world information database management environment. Seven general association types are defined distinguished on basis their structural properties, operational characteristics constraints. They basic constructs an explicit direct complex relationships in characterized by 1. (1) its expressive power offered seven recursive use nested structuring constructs, 2. (2) recognition data such as text, ordered set, matrix, time series, vector, set primitive can be directly manipulated user using DML, (3) support “principle relativism” allowing multiply labeled explicitly specify conflicting views (4) distinction it makes between attributes characterize objects statistically summarize objects, together with statistical operations. A network structure tabular generalized relation or G -relation proposed representing conceptual implementation designs respectively. number restructuring operations algebraic processing G-relations.