Database schema design theory: Achievements and challenges

Abstract

Database schema design is seen as to decide on formats for time-varying instances, on rules for supporting inferences and on semantic constraints. Schema design aims at both faithful formalization of the application and optimization at design time. It is guided by four heuristics: Separation of Aspects, Separation of Specializations, Inferential Completeness and Unique Flavor. A theory of schema design is to investigate these heuristics and to provide insight into how syntactic properties of schemas are related to worthwhile semantic properties, how desirable syntactic properties can be decided or achieved algorithmically, and how the syntactic properties determine costs of storage, queries and updates. Some well-known achievements of design theory for relational databases are reviewed: normal forms, view support, deciding implications of semantic constraints, acyclicity, design algorithms removing forbidden substructures. These achievements should be integrated and generalized from (at least) three viewpoints: one unifying framework, embedding in the full design process, interoperability among databases. Specifically, embedding requires to deal with more advanced semantic notions like null values, recursive query languages, complex objects and object identifiers as well as to explore standard internal database structures and operations like access structure and actual constraint enforcement. All conceptual results should be complemented by detailed cost analysis.KeywordsNormal FormRelational DatabaseAccess StructureLarge Data BaseSemantic ConstraintThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.