We present a probabilistic relational algebra (PRA) which is a generalization of standard relational algebra. Here tuples are assigned probabilistic weights giving the probability that a tuple belongs to a relation. Based on intensional semantics, the tuple weights of the result of a PRA expression always confirm to the underlying probabilistic model. We also show for which expressions extensional semantics yields the same results. Furthermore, we discuss complexity issues and indicate possibilities for optimization. With regard to databases, the approach allows for representing imprecise attribute values, whereas for information retrieval, probabilistic document indexing and probabilistic search term weighting can be modelled. As an important extension, we introduce the concept of vague predicates which yields a probabilistic weight instead of a Boolean value, thus allowing for queries with vague selection conditions. So PRA implements uncertainty and vagueness in combination with the...

this paper we define the semantics of nested relations, which may contain null values, in terms of integrity constraints, called null extended data dependencies, which extend functional dependencies and join dependencies encountered in flat relational database theory. We formalise incomplete information in nested relations by allowing only one unmarked generic null value,

We present a generalisation of the relational data model based on a 4-valued paraconsistent logic. Our data model is capable of manipulating incomplete as well as inconsistent information. For this model, we define algebraic operators that are generalisations of the usual operators, such as union, selection, join, on ordinary relations. Our data model can underlie any database management system that deals with incomplete or inconsistent information. As another application of our model and its algebra, we present a bottomup method for constructing the weak well-founded model of general deductive databases. This method can be very simply extended to construct the well-founded model.

We extend the relational data model to incorporate partial orderings into data domains, which we call the ordered relational model. Within the extended model, we define the Partially Ordered Relational Algebra (the PORA) by allowing the ordering predicate ⊑ to be used in formulae of the selection operator (σ). The PORA expresses exactly the set of all possible relations which are invariant under order-preserving automorphism of databases. This result characterises the expressiveness of the PORA and justifies the development of Ordered SQL (OSQL) as a query language for ordered databases. OSQL provides users with the capability of capturing the semantics of ordered data in many advanced applications, such as those having temporal or incomplete information. Ordered Functional Dependencies (OFDs) on ordered databases are studied, based on two possible extensions of domain orderings: (1) pointwise-ordering and (2) lexicographical ordering. We present a sound and complete axiom system for OFDs in the first case and establish a set of sound and complete chase rules for OFDs in the second. Our results suggest that the implication problems for both cases of OFDs are decidable and that the enforcement of OFDs in ordered relations are practically feasible. In a wider perspective, the proposed model explores an important area of object-relational databases, since ordered domains can be viewed as a general kind of data type. Categories and Subject Descriptors: H.2.1 [Database Management]: Logical Design—data

We describe a database storage extension for geographical metadata, discuss the retrieval requirements of such an extension, and describe the extension process itself. 1 Our aims in undertaking the work reported were twofold: on the one hand we wanted to better understand the basic requirements of a geographical metadata manager, and on the other we wanted to "stress-test" the storage model of our prototype storage system [19]. We discuss the following issues: What are the retrieval requirements of a geographical metadata manager? In what architectural contexts must such a manager operate? How can a database system be extended to meet both these classes of requirements? Characteristic of our approach is that such metadata remains primarily stored in files external to the database system, while indexing and query processing is carried out within the database system. We also report on our experiences in building such a prototype geographical metadata manager. 1 Geographical Metadata a...

Data warehousing is a corporate strategy that needs to integrate information from several sources of separately developed Database Management Systems (DBMSs). A future DBMS of a data warehouse should provide adequate facilities to manage a wide range of information arising from such integration. We propose that the capabilities of database languages should be enhanced to manipulate user-defined data orderings, since business queries in an enterprise usually involve order. We extend the relational model to incorporate partial orderings into data domains and describe the ordered relational model. We have already defined and implemented a minimal extension of SQL, called OSQL, which allows querying over ordered relational databases. One of the important facilities provided by OSQL is that it allows users to capture the underlying semantics of the ordering of the data for a given application. Herein we demonstrate that OSQL aided with a package discipline can be an effective means to manage the interrelated operations and the underlying data domains of a wide range of advanced applications that are vital in data warehousing, such as temporal, incomplete and fuzzy information. We present the details of the generic operations arising from these applications in the form of three OSQL packages called: OSQL_TIME, OSQL_INCOMP and OSQL_FUZZY. Data warehousing is a corporate strategy that addresses a broad range of decision support requirements such as

Imprecise data exist in databases due to their unavailability or data/schema incompatibilities in a multidatabase system. The notion of partial values has been employed for representing imprecise data. Manipulation of partial values is therefore needed for processing queries involving imprecise data. In this paper, we study the problem of eliminating redundant partial values which may result from a projection on an attribute with partial values. The redundancy of partial values is de ned through the interpretation of a set of partial values. This problem is equivalent to searching a minimal semantically-equivalent subset of a set of partial values. A semantically-equivalent subset contains exactly the same information as the original set. We derive a set of useful properties and apply a graph matching technique to develop an e cient algorithm for searching such a minimal subset and therefore eliminating redundant partial values. By this process, we not only provide a concise answer to the user, but also reduce the communication cost when partial values are requested to be transmitted from one site to another site in a distributed environment. Moreover, further manipulation of the partial values can be simpli ed. Finally,

Abstract not found