Extending the possibilistic data model with one-level nested relations

The paper is situated in the area of databases containing ill-known attribute values represented by possibility distributions. In order to manipulate such databases in a safe and efficient way, a constrained framework has been previously suggested, where a restricted number of querying operations are permitted (selections and fk-joins calling on attributes taking imprecise values). The key for efficiency resides in the fact that these operators do not require computations to be made explicitly over all the more or less possible worlds. However, this framework has several limitations and an extended model based on the notion of nested relations enabling representation of possibility distributions over sets of attributes is proposed