Full hierarchical dependencies in fixed and undetermined universes

Full hierarchical dependencies (FHDs) constitute a large class of relational dependencies. A relation exhibits an FHD precisely when it is the natural join over at least two of its projections that all share the same join attributes. Therefore, FHDs generalise multivalued dependencies (MVDs) in which case the number of these projections is precisely two. The implication of FHDs has originally been defined in the context of some fixed finite universe. This paper identifies a sound and complete set of inference rules for the implication of FHDs. This axiomatisation is very reminiscent of that for MVDs. Then, an alternative notion of FHD implication is introduced in which the underlying set of attributes is left undetermined. The first main result establishes a finite axiomatisation for FHD implication in undetermined universes. It is then formally clarified that the complementation rule is only a mere means for database normalisation. In fact, the second main result establishes a finite axiomatisation for FHD implication in fixed universes which allows to infer FHDs either without using the complementation rule at all or only in the very last step of the inference. This also characterises the expressiveness of an incomplete set of inference rules in fixed universes. The results extend previous work on MVDs by Biskup.     

Charting the completeness frontier of inference systems for multivalued dependencies

The implication of multivalued dependencies in relational databases has originally been defined in the context of some fixed finite universe. While axiomatisability and implication problems have been intensely studied with respect to this notion almost no research has been devoted towards the alternative notion of implication in which the underlying universe of attributes is left undetermined. Based on a set of common inference rules we establish all axiomatisations in undetermined universes, and all axiomatisations in fixed universes that indicate the role of the complementation rule as a means of database normalisation. This characterises the expressiveness of several incomplete sets of inference rules. We also establish relationships between axiomatisations in fixed and undetermined universes, and study the time complexity of the implication problem in undetermined universes. The results of this paper establish a foundation for reasoning about multivalued dependencies without the assumption of a fixed underlying universe.     

Complexity of dimension three and some related edge-covering characteristics of graphs

We study systems of inference rules for multivalued dependencies in database relations. For such systems we define a new notion of completeness in which the underlying universe of attributes is left undetermined, whereas the earlier studied concept of completeness refers to a fixed finite universe. We introduce a new inference rule, the subset rule, and using this rule we prove that a certain system is complete. Furthermore we clarify the role of the so-called complementation rule.     

XML多值依赖的推理规则集问题

XML多值依赖的推理规则集问题是解决XML数据依赖的蕴涵问题的基础,是XML规范化理论的关键问题之一。该文对XML树、树元组等进行了重新定义,与Vincent等人不同,提出了基于DTD的XML多值依赖的概念,通过对XML的关系化表示给出了其形式化定义,定义了XML多值依赖集的闭包、XML多值依赖路径依赖基以及XML多值依赖路径集的闭包等概念,给出了一个有效且完备的推理规则集,并对其有效性及完备性进行了证明。     

On the complementation rule for multivalued dependencies in database relations

Summary We study the interrelation between various versions of the complementation rule and other inference rules for multivalued dependencies in database relations. In particular we settle two open questions of [1] concerning the derivability of inference rules for Boolean operations on the right side of multivalued dependencies. Furthermore we prove that there is a trade-off between the complementation rule and the augmentation rule.     

Characterisations of multivalued dependency implication over undetermined universes

In relational databases the original definition of a multivalued dependency is dependent on the underlying relation schema. In this context, the implication of multivalued dependencies has been characterised from multiple perspectives. Logically, it is equivalent to the logical implication of certain material implications in Boolean propositional logic. Proof-theoretically, the Chase procedure offers a convenient tool to decide implication. And algebraically, the implication can be characterised by the notion of closed attribute sets with respect to multivalued dependencies. The assumption of having a fixed underlying relation schema is not always feasible in practice, and also distinguishes multivalued dependencies from other classes of data dependencies. In this paper, we establish logical, proof-theoretical and algebraic characterisations for Biskup?s notion of multivalued dependency implication over undetermined universes. That is, we unburden the current theory of the assumption of having a fixed underlying relation schema. From the perspective of probability theory this means that is unnecessary to fix the set of discrete probabilistic variables in order to utilise conditional independencies.     

Some results on the deductive structure of join dependencies

Among the many different data dependencies defined, the so-called join dependencies play a central role, since they explicitly capture lossless join properties for relation schemes.In this paper we state some inference rules for join dependencies and embedded join dependencies. A set of two rules is shown to be complete for monadic join dependency inferences (inferences from a single dependency). Furthermore, it is shown that there is no finite set of inference rules that is complete for embedded join dependencies.     

An algebraic theory of functional and multivalued dependencies in relational databases

Computation of the dependency basis is the fundamental step in solving the membership problem for functional dependencies (FDs) and multivalued dependencies (MVDs) in relational database theory. We examine this problem from an algebraic perspective. We introduce the notion of the inference basis of a set M of MVDs and show that it contains the maximum information about the logical consequences of M. We propose the notion of a dependency-lattice and develop an algebraic characterization of inference basis using simple notions from lattice theory. We also establish several interesting properties of dependency-lattices related to the implication problem. Founded on our characterization, we synthesize efficient algorithms for (a): computing the inference basis of a given set M of MVDs; (b): computing the dependency basis of a given attribute set w.r.t. M; and (c): solving the membership problem for MVDs. We also show that our results naturally extend to incorporate FDs also in a way that enables the solution of the membership problem for both FDs and MVDs put together. We finally show that our algorithms are more efficient than existing ones, when used to solve what we term the ‘generalized membership problem’.     

A universal formalism to express decompositions,functional dependencies and other constraints in a relational database

A general formalism, called the general dependencies, is presented. The multivalued, mutual, join and functional dependencies can be expressed in this formalism. Some properties of general dependencies are stated and their influence on the decompositionand the partial decomposition of a relation is studied.The class of general dependencies is compared with other classes of dependencies.It is proved that every set of functional dependencies can be expressed by a single general dependency. The same property holds for the multivalued dependencies.Finally the concept of functional dependency is generalized.     

The theory of functional and template dependencies

Template dependencies were introduced by Sadri and Ullman [17] to generalize existing forms of data dependencies. It was hoped that by studying a large and natural class of dependencies, we could solve the inference problem for these dependencies, while that problem was elusive for restricted subsets of the template dependencies, such as embedded multivalued dependencies. At about the same time, other generalizations of known dependency forms were developed, such as the implicational dependencies of Fagin [11] and the algebraic dependencies of Yannakakis and Papadimitriou [20]. Unlike the template dependencies, the latter forms include the functional dependencies as special cases. In this paper we show that no nontrivial functional dependency follows from template dependencies, and we characterize those template dependencies that follow from functional dependencies. We then give a complete set of axioms for reasoning about combinations of functional and template dependencies. As a result, template dependencies augmented by functional dependencies can serve as a substitute for the more general implicational or algebraic dependencies, providing the same ability to represent those dependencies that appear ‘in nature’, while providing a somewhat simpler notation and set of axioms than the more general classes.     

具有多时间粒度的时态多值依赖及时态模式分解方法研究

一个好的数据库逻辑设计目标是消除数据冗余以及插入、删除和更新异常.对于时态数据库,通过具有多时间粒度的时态函数依赖约束对时态数据库进行规范化已有大量研究.基于时态函数依赖和多值依赖理论提出了多时间粒度约束的时态多值依赖(TMVD)等概念,并给出了时态多值依赖的推理规则,对其有效性、完备性进行了证明.由于包含有限个TMVD的TMVD集通常蕴含着无限个TMVD,给出了TMVD的有限推理规则,对其有效性、完备性进行了证明.最后,基于时态多值依赖集提出了时态第四范式,并给出了时态模式的T4NF的无损分解算法,对算法的可终止性、正确性进行了证明, 并对时间复杂度进行了分析.     

Another view of functional and multivalued dependencies in the relational database model

In this paper, pseudo-functional and pseudo-multivalued dependencies are introduced. They are shown to be isomorphic with functional and multivalued dependencies, i.e., they behave in the same way with respect to implication. This formalism leads in a very natural way to a rather efficient algorithm for the inference of functional and multivalued dependencies. Some applications to acyclic join dependencies are discussed.     

Fuzzy data compression based on data dependencies

In this article, we focus on the issues of fuzzy data dependencies. After introducing the notion of semantic equivalence degree, fuzzy functional and multivalued dependencies are defined. A set of sound and complete inference rules, similar to Armstrong's axioms for classic cases, for fuzzy functional dependencies (FFDs) and fuzzy multivalued dependencies (FMVDs) are proposed. The strategies and approaches for compressing fuzzy values by FFDs and FMVDs are investigated. By such processing, the unnecessary elements are eliminated from a fuzzy value and its range is compressed. © 2002 Wiley Periodicals, Inc.     

Controlling FD and MVD inferences in multilevel relational databasesystems

The authors investigate the inference problems due to functional dependencies (FD) and multivalued dependencies (MVD) in a multilevel relational database (MDB) with attribute and record classification schemes, respectively. The set of functional dependencies to be taken into account in order to prevent FD-compromises is determined. It is proven that incurring minimum information loss to prevent compromises is an NP-complete problem. An exact algorithm to adjust the attribute levels so that no compromise due to functional dependencies occurs is given. Some necessary and sufficient conditions for MVD-compromises are presented. The set of MVDs to be taken into account for controlling inferences is determined. An algorithm to prevent MVD-compromises in a relation with conflict-free MVDs is given     

时态函数依赖多值依赖混合集的成员籍问题研究

对于TFD和TMVD混合集约束的时态模式来说,由于多时间粒度的使用使成员籍问题的解决变得更加复杂.由于成员籍问题的解决对设计有效的模式分解算法必不可少,由此定义了时态类型集的强封闭集、属性集的有限闭包、属性集在给定时态类型上的有限依赖基、属性集的有限依赖基及特殊有限依赖基等概念,给出了求属性集的有限闭包、有限依赖基和特殊有限依赖基、时态混合集成员籍问题的算法,并对算法的可终止性、正确性进行了证明,对时间复杂性进行了分析.     

An Infornation-Theoretic Analysis of Relational Databases—Part I: Data Dependencies and Information Metric

Database design is based on the concept of data dependency, which is the interrelationship between data contained in various sets of attributes. In particular, functional, multivalued and acyclic join, dependencies play an essential role in the design of database schemas. The basic definition of an information metric and how this notion can be used in relational database are discussed in this paper. We use Shannon entropy as an information metric to quantify the information associated with a set of attributes. Thus, we prove that data dependencies can be formulated in terms of entropies. These formulas make the numerical computation and testing of data dependencies feasible. Among the different types of data dependencies, the acyclic join dependency is most important to the design of a relational database schema. The acyclic join dependency, with multivalued dependency as a special case, impose a constraint on the information-preserving decomposition of a relation. It is interesting that this constraint on a relation is similar to Gibbs' condition for separating physical systems in statistical mechanics. They both assert that entropy is preserved during the decomposition process. That is, the entropies of the corresponding set of attributes must satisfy the inclusion–exclusion identity.     

A top-down proof procedure for generalized data dependencies

Data dependencies are well known in the context of relational database. They aim to specify constraints that the data must satisfy to model correctly the part of the world under consideration. The implication problem for dependencies is to decide whether a given dependency is logically implied by a given set of dependencies. A proof procedure for the implication problem, called “chase”, has already been studied in the generalized case of tuple-generating and equality-generating dependencies. The chase is a bottom-up procedure: from hypotheses to conclusion, and thus is not goal-directed. It also entails in the case of TGDs the dynamic creation of new constants, which can turn out to be a costly operation. This paper introduces a new proof procedure which is top-down: from conclusion to hypothesis, that is goal-directed. The originality of this procedure is that it does not act as classical theorem proving procedures, which require a special form of expressions, such as clausal form, obtained after Skolemization. We show, with our procedure, that this step is useless, and that the notion of piece allows infering directly on dependencies, thus saving the cost of Skolemizing the dependencies set and, morever, that the inference can be performed without dynamically creating new constants. Although top-down approaches are known to be less efficient in time than bottom-up ones, the notion of piece cuts down irrelevant goals usually generated, leading to a usable top-down method. With the more recent introduction of constrained and ordered dependencies, some interesting perspectives also arise. Received: 16 October 2000 / 11 May 2002     

XML上的函数依赖推理

函数依赖是数据语义的重要组成部分,这一概念被引入到XML的领域中.基于DTD,XML的树模型和路径表达式,对节点的值相等和路径节点集作了定义.在此基础上,研究了XML中函数依赖、逻辑蕴涵和路径闭包的概念,证明了函数依赖在给定DTD上的可满足性.提出了一个XML上函数依赖的正确和完备的推理规则集,并给出了一个用于计算路径闭包的算法.     

The implication problem for ‘closest node’ functional dependencies in complete XML documents

With the growing use of XML as a format for the permanent storage of data, the study of functional dependencies in XML (XFDs) is of fundamental importance in a number of areas such as understanding how to effectively design XML databases without redundancy or update problems, and data integration. In this article we investigate a particular type of XFD, called a weak ‘closest node’ XFD, that has been shown to extend the classical notion of a functional dependency in relational databases. More specifically, we investigate the implication problem for weak ‘closest node’ XFDs in the context of XML documents with no missing information. The implication problem is the most important one in dependency theory, and is the problem of determining if a set of dependencies logically implies another dependency. Our first, and main, contribution is to provide an axiom system for XFD implication. We prove that our axiom system is both sound and complete, and we then use this result to develop a sound and complete quadratic time closure algorithm for XFD implication. Our second contribution is to investigate the implication problem for XFDs in the presence of a Document Type Definition (DTD). We show that for a class of DTDs called structured DTDs, the implication problem for a set of XFDs and a structured DTD can be converted to the implication problem for a set of XFDs alone, and so is axiomatizable and efficiently solvable by the first contribution. We do this by augmenting the original set of XFDs with additional XFDs generated from the structure of the DTD.     

Adding inclusion dependencies to an object-oriented data model with uniqueness constraints

We study an object-oriented data model that allows to express both uniqueness constraints and inclusion dependencies as semantic constraints. The data model is based on a subset of F-logic. Uniqueness constraints comprise path functional dependencies which generalise functional dependencies and reflect the navigational power of object-oriented query languages. As inclusion dependencies, we consider explicit class inclusion constraints, besides inclusions required by class hierarchies, and onto constraints that enforce reachability of objects. For these classes of semantic constraints we present an axiomatisation and prove its inference rules to be correct and complete with respect to general logical implication, leaving the decision problem open. The completeness proof combines the known construction for path functional dependencies alone with a possibly infinite model generation process to enforce onto constraints. The results prepare the grounds for normal forms in object-oriented data models and subsequently for computer aided object-oriented database design, following the decomposition approach for the relational data model. Beyond the application for schema design, the achievements could also be exploited for related tasks like semantic query optimisation and mediated data integration within a variety of graph based data models. Received: 11 October 2000 / 27 January 2003