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Many multilevel relational models have been proposed; different models offer different advantages. In this paper, we adapt and refine several of the best ideas from previous models and add new ones to build the new Multilevel Relational (MLR) data model. MLR provides multilevel relations with element-level labeling as a natural extension of the traditional relational data model. MLR introduces several new concepts (notably, data-borrow integrity and the UPLEVEL statement) and significantly redefines existing concepts (polyinstantiation and referential integrity as well as data manipulation operations). A central contribution of this paper is proofs of soundness, completeness, and security of MLR. A new data-based semantics is given for the MLR data model by combining ideas from SeaView, belief-based semantics, and LDV. This new semantics has the advantages of both eliminating ambiguity and retaining upward information flow. MLR is secure, unambiguous, and powerful. It has five integrity properties and five operations for manipulating multilevel relations. Soundness, completeness, and security show that any of the five database manipulation operations will keep database states legal (i.e., satisfy all integrity properties), that every legal database state can be constructed, and that MLR is noninterfering. The expressive power of MLR also compares favorably with several other models.
Sandhu et al. (Sun,) studied this question.
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