During the last three or four years several investigators have been exploring “semantic models ” for formatted databases. The intent is to capture (in a more or less formal way) more of the meaning of the data so that database design can become more systematic and the database system itself can behave more intelligently. Two major thrusts are clear: (I) the search for meaningful units that are as small as possible--atomic semantics; (2) the search for meaningful units that are larger than the usual n-ary relation-molecular semantics. In this paper we propose extensions to the relational model to support certain atomic and molecular semantics. These extensions represent a synthesis of many ideas from the published work in semantic modeling plus the introduction of new rules for insertion, update, and deletion, as well as new algebraic operators.

this paper we briefly review some of these issues and then concentrate on the problem of generalizing the formal framework of the relational data model to include null values. A basic problem with null values is that they have many plausible interpretations. The ANSI/SPARC interim report, for instance, cites 14 different manifestations of nulls. Most authors, however, agree that the various manifestations of nulls can be reduced to two basic interpretations. These are: (a) the unknown interpretation: a value exists but it is not known; and lb) the nonexistent interpretation: a value does not exist

Background material is presented on deductive and normal deductive databases. A historical review is presented of work in disjunctive deductive databases, starting from 1982. The semantics of alternative classes of disjunctive databases is reviewed with their model and fixpoint characterizations. Algorithms are developed to compute answers to queries in the alternative theories using the concept of a model tree. Open problems in this area are discussed.

Databases are increasingly being used to store information covered by heterogeneous policies, which require support for access control with great flexibility. This has led to increasing interest in using fine-grained access control, where different cells in a relation may be governed by different access control rules. Although several proposals have been made to support fine-grained access control, there currently does not exist a formal notion of correctness regarding the query answering procedure. In this paper, we propose such a formal notion of correctness in fine-grained database access control, and discuss why existing approaches fall short in some circumstances. We then propose a labeling approach for masking unauthorized information and a query evaluation algorithm which better supports fine-grained access control. Finally, we implement our algorithm using query modification and evaluate its performance.

. Inaccessibility of part of the database is a research topic hardly addressed in the literature about distributed databases. However, there are various application areas, where the database has to remain operable even if part of the database is inaccessible. In particular, queries to the database should be processed in an appropriate way. This means that the final and all intermediate results of a query in a distributed database system must be regarded as potentially vague. In this paper we propose hybrid representations for vague sets, vague multisets, and vague lists, which address the accessible elements in an enumerating part and the inaccessible elements in a descriptive part. These representations allow to redefine the usual query language operations for vague sets, vague multisets, and vague lists. The main advantage of our approach is that the descriptive part of the representation can be used to improve the enumerating part during query processing. 1 Addressed P...

this paper was written, the use of null values was widespread. Indeed, the rst use of null values in the context of relational algebra was contained in a paper written by Codd in 1975 paper [3], and the ANSI/X3/SPARC interim report [1] published the same year included 14 dierent ways in which null values might be interpreted suggesting wide acceptance of their use. The omissions were various. The most serious was that of the work of Grant, who was working on the problem of incomplete information as early as 1974 [8], and who took Codd's initial results on null values in relational algebra and extended them considerably. The rst extension [7] involved a slight alteration to Codd's three-valued logic to ensure that it retrieved the right tuples in all situations. The next extension [6] was to handle what Grant calls "partial values", that is values which are known to lie in an interval and so are partially determined, and this idea was further developed in [5]. This line of research

Abstract — SQL is one of the major languages to manipulate and retrieve data in the databases. It was standardized by the corporation among researchers and commercial database industries into many versions. SQL provides NULL values for attributes which are unknown to the user. There are three meanings of NULL but they are not classified by database engines. Results of SQL queries show different meaning when they are produced by subqueries or atomic predicates. This paper explains the meaning of them with suggestions proposing to database community.

Abstract — One of the major language to manipulate databases is SQL which is standardized by the corporation among researchers and commercial database industries. SQL provides NULL values for attributes which are unknown to the user. There are three meanings of NULL but they are not classified by database engines. Results of SQL queries show different meaning when they are produced by subqueries. This paper explains the meaning of them with suggestions proposing to database community. Index Terms—Database Engines, Null, SQL, Subquery I.

Uncertain data in databases were originally denoted as null values, which were later generalized to partial values. Based on the concept of partial values, we have further generalized the notion to probabilistic partial values. In this paper, an important operation -- division, is fully studied to handle partial values and probabilistic partial values. Due to the uncertainty of partial values and probabilistic partial values, the corresponding extended division may produce maybe tuplesand maybe tuples with degrees of uncertainty, respectively. To process this extended division, we decompose a relation consisting of partial values or probabilistic partial values into a set of relations containing only de nite values. Bipartite graph matching techniques are then applied to develop e cient algorithms for the extended division that handles partial values. The re nement on the maybe result is also discussed. Finally, we study the extended division that handles probabilistic partial

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,