INCOMPLETE RELATIONAL DATABASE MODELS BASED ON INTERVALS

In this paper, we utilize intervals for unknown values in incomplete r elational databases. We use tables to represent unknown relations. Fir st, we define three partial tuple types in a table to specify incomple teness relationships among tuples of the same table. For tuples of dif ferent tables, we distinguish between the cases where incompleteness i s introduced at the relation level, tuple level, or attribute value le vel. Also, based on these relationships among tuples in different tabl es, we present a family of incomplete relational database models. For each of the models, we show that query evaluation is sound (i.e., no i ncorrect results are derivable) in the Imielinski-Lipski sense. None o f the models is complete (i.e., all valid conclusions are derivable) i n the Imielinski-Lipski sense. We briefly compare two of the models in the family with other approaches. Considering each table tuple as a s et of d-dimensional cubes, each model in the family of models presente d in this paper can be considered and implemented as a geometric datab ase model. We briefly summarize the geometric operations and the primi tive update semantics that need to be utilized in such an implementati on.