A logic-based integration of active and deductive databases

A logic-based approach to the specification of active database functionality is presented which not only endows active databases with a well-defined and well-understood formal semantics, but also tightly integrates them with deductive databases. The problem of endowing deductive databases with rule-based active behaviour has been addressed in different ways. Typical approaches include accounting for active behaviour by extending the operational semantics of deductive databases, or, conversely, accounting for deductive capabilities by constraining the operational semantics of active databases. The main contribution of the paper is an alternative approach in which a class of active databases is defined whose operational semantics is naturally integrated with the operational semantics of deductive databases without either of them strictly subsuming the other. The approach is demonstrated via the formalization of the syntax and semantics of an active-rule language that can be smoothly incorporated into existing deductive databases, due to the fact that the standard formalization of deductive databases is reused, rather than altered or extended. One distinctive feature of the paper is its use of ahistory, as defined in the Kowalski-Sergot event-calculus, to define event occurrences, database states and actions on these. This has proved to be a suitable foundation for a comprehensive logical account of the concept set underpinning active databases. The paper thus contributes a logical perspective to the ongoing task of developing a formal theory of active databases. Alvaro Adolfo Antunes Fernandes, Ph.D.: He received a B.Sc. in Economics (Rio de Janeiro, 1984), an M.Sc. in Knowledge-Based Systems (Edinburgh, 1990) and a Ph.D. in Computer Science (Heriot-Watt, 1995). He worked as a Research Associate at Heriot-Watt University from December 1990 until December 1995. In January 1996 he joined the Department of Mathematical and Computing Sciences at Goldsmiths College, University of London, as a Lecturer. His current research interests include advanced data- and knowledge-base technology, logic programming, and software engineering. M. Howard Williams, Ph.D., D.Sc.: He obtained his Ph.D. in ionospheric physics and recently a D.Sc. in Computer Science. He was appointed as the first lecturer in Computer Science at Rhodes University in 1970. During the following decade he rose to Professor of Computer Science and in 1980 was appointed as Professor of Computer Science at Heriot-Watt University. From 1980 to 1988 he served as Head of Department and then as director of research until 1992. He is now head of the Database Research Group at Heriot-Watt University. His current research interests include active databases, deductive objectoriented databases, spatial databases, parallel databases and telemedicine. Norman W. Paton, Ph.D.: He received a B.Sc. in Computing Science from the University of Aberdeen in 1986. From 1986 to 1989 he worked as a Research Assistant at the University of Aberdeen, receiving a Ph. D. in 1989. From 1989 to 1995 he was a Lecturer in Computer Science at Heriot-Watt University. Since July 1995, he has been a Senior Lecturer in Department of Computer Science at the University of Manchester. His current research interests include active databases, deductive object-oriented databases, spatial databases and database interfaces.     

Mining frequent conjunctive queries using functional and inclusion dependencies

We address the issue of mining frequent conjunctive queries in a relational database, a problem known to be intractable even for conjunctive queries over a single table. In this article, we show that mining frequent projection-selection-join queries becomes tractable if joins are performed along keys and foreign keys, in a database satisfying functional and inclusion dependencies, under certain restrictions. We note that these restrictions cover most practical cases, including databases operating over star schemas, snow-flake schemas and constellation schemas. In our approach, we define an equivalence relation over queries using a pre-ordering with respect to which the support is shown to be anti-monotonic. We propose a level-wise algorithm for computing all frequent queries by exploiting the fact that equivalent queries have the same support. We report on experiments showing that, in our context, mining frequent projection-selection-join queries is indeed tractable, even for large data sets.     

The design of optimal access paths for relational databases

A generalized model for the performance optimization of physical relational database access has been developed and implemented. The model consists of a set of algorithms and cost equations. It assists the database designer in specifying and selecting optimal access schemes within given systems' constraints. The model is an extension of previous work. It is more comprehensive and flexible. It addresses problem that have not been considered in previous models; it integrates into one model aspects that were treated individually before, and it produces database access configurations that can work within certain given system constraints.     

一种从关系数据库向Flogic本体转换的方法

目前提出的从关系数据库中获取本体的方法主要关注主键之间的相关性,导致抽取的语义信息不全。本文提出一种将关系数据库向Flogic表示的本体转换的方法,该方法通过对主键、数据、属性相关性的综合分析,可以抽取出关系数据库中隐含的语义信息,如继承关系及优化结构。     

Deciding implication for functional dependencies in complex-value databases

Modern applications increasingly require the storage of data beyond relational structure. The challenge of providing well-founded data models that can handle complex objects such as lists, sets, multisets, unions and references has not been met yet in a completely satisfactory way. The success of such data models will greatly depend on the existence of automated database design techniques that generalise achievements from relational databases. In this paper, we study the implication problem of functional dependencies (FDs) in the presence of records, sets, multisets and lists. Database schemata are defined as nested attributes, database instances as nested relations and FDs are defined in terms of subattributes of the database schema. The expressiveness of FDs deviates fundamentally from previous approaches in different data models including the nested relational data model and XML.     

A note on approximation measures for multi-valued dependencies in relational databases

We consider the problem of defining a normalized approximation measure for multi-valued dependencies in relational database theory. An approximation measure is a function mapping relation instances to real numbers. The number to which an instance is mapped, intuitively, describes the strength of the dependency in that instance. A normalized approximation measure for functional dependencies has been proposed previously: the minimum number of tuples that need be removed for the functional dependency to hold divided by the total number of tuples. This leads naturally to a normalized measure for multi-valued dependencies: the minimum number of tuples that need be removed for the multi-valued dependency to hold divided by the total number of tuples.The measure for functional dependencies can be computed efficiently, O(|r|log(|r|)) where |r| is the relation instance. However, we show that an efficient algorithm for computing the analogous measure for multi-valued dependencies is not likely to exist. A polynomial time algorithm for computing the measure would lead to a polynomial time algorithm for an NP-complete problem (proven by a reduction from the maximum edge biclique problem in graph theory). Hence, we argue that it is not a good measure. We propose an alternate measure based on the lossless join characterization of multi-valued dependencies. This measure is efficiently computable, O(|r|²).     

Bottom-up computation of the Fitting model for general deductive databases

General logic programs are those that contain both positive and negative subgoals in their clause bodies. For such programs Fitting proposed an elegant 3-valued minimum model semantics that avoids some impracticalities of previous approaches. Here we present a method to compute this Fitting model for deductive databases. We introducepartial relations, which are the semantic objects associated with predicate symbols, and define algebraic operators over them. The first step in our model computation method is to convert the database rules into partial relation definitions involving these operators. The second step is to build the minimum model iteratively. We give algorithms for both steps and show their termination and correctness. We also suggest extensions to our method for computing the well-founded model proposed by van Gelder, Ross and Schlipf.     

基于数据流的滑动窗口机制的研究

传统的关系数据库是在持久稳定的数据集合上进行数据查询,而数据流的长度是无界的,不可能将所有的数据存储下来,因此对数据流的查询处理大多采用了持续查询。对数据流进行持续查询时,往往感兴趣的不是所有的数据而是最近到达的部分数据,这样就引入滑动窗口模型。定义滑动窗口语义是数据流管理系统中一个非常基础性的工作,直接关系到数据流的存储和查询的执行效率。针对滑动窗口的模型和语义进行了研究。     

Effective utilization of copies in a transparent distributed environment

In a distributed relational database system, the processing of a query involves data transmission among different sites via a computer network. In a distributed database multiple copies of each relation can be allocated to different, physically distributed sites. In this paper we discuss the query preoptimization problem for join-queries. In general, there is a large number of possibilities to use the copies of the data item in a distributed relational database when evaluating a join-query. We consider the problem of a copy preselection for each relation in a join sequence of a join-query. We show how to express the preselection problem for a given query and data allocation to the network in terms of an integer linear programming problem, namely, a minimum cover problem. It can be treated as a heuristic for the first phase of a join-query optimization, and as such as an input to the final stage of optimization, the execution strategy generation for a join-query. In this paper we assumed that a distributed system provides fully transparent data management, i.e., data allocation to the network and data replication which is revealed to a user. We illustrate the proposed mathematical programming problem through a nontrivial example. Recommended by: R. Elamsri     

Change impact analysis for requirements: A metamodeling approach

ContextFollowing the evolution of the business needs, the requirements of software systems change continuously and new requirements emerge frequently. Requirements documents are often textual artifacts with structure not explicitly given. When a change in a requirements document is introduced, the requirements engineer may have to manually analyze all the requirements for a single change. This may result in neglecting the actual impact of a change. Consequently, the cost of implementing a change may become several times higher than expected.ObjectiveIn this paper, we aim at improving change impact analysis in requirements by using formal semantics of requirements relations and requirements change types.MethodIn our previous work we present a requirements metamodel with commonly used requirements relation types and their semantics formalized in first-order logic. In this paper the classification of requirements changes based on structure of a textual requirement is provided with formal semantics. The formalization of requirements relations and changes is used for propagating proposed changes and consistency checking of proposed changes in requirements models. The tool support for change impact analysis in requirements models is an extension of our Tool for Requirements Inferencing and Consistency Checking (TRIC).ResultsThe described approach for change impact analysis helps in the elimination of some false positive impacts in change propagation, and enables consistency checking of changes.ConclusionWe illustrate our approach in an example which shows that the formal semantics of requirements relations and change classification enables change alternatives to be proposed semi-automatically, the reduction of some false positive impacts and contradicting changes in requirements to be determined.     

A complete temporal relational algebra

Various temporal extensions to the relational model have been proposed. All of these, however, deviate significantly from the original relational model. This paper presents a temporal extension of the relational algebra that is not significantly different from the original relational model, yet is at least as expressive as any of the previous approaches. This algebra employs multidimensional tuple time-stamping to capture the complete temporal behavior of data. The basic relational operations are redefined as consistent extensions of the existing operations in a manner that preserves the basic algebraic equivalences of the snapshot (i.e., conventional static) algebra. A new operation, namely temporal projection, is introduced. The complete update semantics are formally specified and aggregate functions are defined. The algebra is closed, and reduces to the snapshot algebra. It is also shown to be at least as expressive as the calculus-based temporal query language TQuel. In order to assess the algebra, it is evaluated using a set of twenty-six criteria proposed in the literature, and compared to existing temporal relational algebras. The proposed algebra appears to satisfy more criteria than any other existing algebra. Edited by Wesley Chu. Received February 1993 / Accepted April 1995     

A Reasoning Mechanism for DeductiveObject-Oriented Databases

Based on the approach implementing a deductive object-oriented database system through the underlying relational database,this paper presents and object reasoning language O-Datalog,which is the extension of Datalog in form and can deal with object-oriented data.For any O-Datalog program,an dquivalent Datalog program can be built to help evaluate the original program.This paper focuses on the syntax,semantics and evaluation of O-Datalog.     

A logic-based mechanism for integrity maintenance of engineering databases

The semantics of engineering data can be represented in terms of constraints and can be maintained via constraint checking and enforcement. Conventional databases (e.g. Relational Databases) are inadequate for maintaining engineering data semantics because they have no effective means for representing and checking/enforcing constrains. As an extension of relational databases, deductive databases overcome this inadequacy by enabling constraint representation and checking. However, they too lack the constraint enforcement ability. a logic-based mechanism for enforcing constrainst in deductive databases is presented in this paper. The mechanism is composed of two operators: a truth enforcement operator and a falsity enforcement operator. The mechanics of these operators and their use for integrity enfocement are described herein.     

PRL: A probabilistic relational language

In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into a logic programming framework. We show how to represent varying degrees of complexity in the semantics including attribute uncertainty, structural uncertainty and identity uncertainty. Our approach is similar in spirit to the work in Bayesian Logic Programs (BLPs), and Logical Bayesian Networks (LBNs). However, surprisingly, there are still some important differences in the resulting formalism; for example, we introduce a general notion of aggregates based on the PRM approaches. One of our contributions is that we show how to support richer forms of structural uncertainty in a probabilistic logical language than have been previously described. Our goal in this work is to present a unifying framework that supports all of the types of relational uncertainty yet is based on logic programming formalisms. We also believe that it facilitates understanding the relationship between the frame-based approaches and alternate logic programming approaches, and allows greater transfer of ideas between them. Editors: Hendrik Blockeel, David Jensen and Stefan Kramer An erratum to this article is available at .     

Minimal model generation for refined answering of generalized queries in disjunctive deductive databases

Generalized queries are defined as sets of clauses in implication form. They cover several tasks of practical importance for database maintenance such as answering positive queries, computing database completions and integrity constraints checking. We address the issue of answering generalized queries under the minimal model semantics for the class of disjunctive deductive databases (DDDBs). The advanced approach is based on having the query induce an order on the models returned by a sound and complete minimal model generating procedure. We consider answers that are true in all and those that are true in some minimal models of the theory. We address the issue of answering positive queries through the construction of the minimal model state of the DDDB, using a minimal model generating procedure. The refinements allowed by the procedure include isolating a minimal component of a disjunctive answer, the specification of possible updates to the theory to enable the derivability of certain queries and deciding the monotonicity properties of answers to different classes of queries.     

Using Constraint Programming in Selection Operators for Constraint Databases

Constraint Databases represent complex data by means of formulas described by constraints (equations, inequations or Boolean combinations of both). Commercial database management systems allow the storage and efficient retrieval of classic data, but for complex data a made-to-measure solution combined with expert systems for each type of problem are necessary. Therefore, in the same way as commercial solutions of relational databases permit storing and querying classic data, we propose an extension of the Selection Operator for complex data stored, and an extension of SQL language for the case where both classic and constraint data need to be managed. This extension shields the user from unnecessary details on how the information is stored and how the queries are evaluated, thereby enlarging the capacity of expressiveness for any commercial database management system. In order to minimize the selection time, a set of strategies have been proposed, which combine the advantages of relational algebra and constraint data representation.     

Temporal data exchange

Data exchange is the problem of transforming data that is structured under a source schema into data structured under another schema, called the target schema, so that both the source and target data satisfy the relationship between the schemas. Many applications such as planning, scheduling, medical and fraud detection systems, require data exchange in the context of temporal data. Even though the formal framework of data exchange for relational database systems is well-established, it does not immediately carry over to the settings of temporal data, which necessitates reasoning over unbounded periods of time.In this work, we study data exchange for temporal data. We first motivate the need for two views of temporal data: the concrete view, which depicts how temporal data is compactly represented and on which the implementations are based, and the abstract view, which defines the semantics of temporal data as a sequence of snapshots. We first extend the chase procedure for the abstract view to have a conceptual basis for the data exchange for temporal databases. Considering non-temporal source-to-target tuple generating dependencies and equality generating dependencies, the chase algorithm can be applied on each snapshot independently. Then we define a chase procedure (called c-chase) on concrete instances and show the result of c-chase on a concrete instance is semantically aligned with the result of chase on the corresponding abstract instance. In order to interpret intervals as constants while checking if a dependency or a query is satisfied by a concrete database, we will normalize the instance with respect to the dependency or the query. To obtain the semantic alignment, the nulls (which are introduced by data exchange and model incompleteness) in the concrete view are annotated with temporal information. Furthermore, we show that the result of the concrete chase provides a foundation for query answering. We define naïve evaluation on the result of the c-chase and show it produces certain answers.     

About quotient and division of crisp and fuzzy relations

The role and properties of the division are very well known in the context of queries addressed to regular relational databases. However, Boolean queries whose result is expressed in terms of all or nothing may turn out to be too limited to answer certain user needs and it is desirable to envisage extended queries by introducing preferences in the conditions. In this paper, two lines of extension of the division operator are studied: (i) operand relations of the division are fuzzy relations (i.e., they are made of weighted tuples) and (ii) the universal quantifier underlying the division is weakened. Various approaches to these extensions can be considered and one of our goals is to point out those which ensure that the resulting relation is a quotient (in reference to the characterization of the quotient of two integers). So doing, a sound semantics for the extended division is guaranteed.     

Toward the Next Generation of Data Modeling Tools

This paper describes the Update Protocol Model (UPM), a formal language for the expression of database update semantics. UPM has been used primarily to capture and communicate in a precise and uniform notation the plethora of database semantics described by a variety of "fourth generation" models, many of which are imprecise when it comes to update semantics. Several computing trends–knowledge-based expert systems, distributed database management systems, and new applications based on higher order semantic models–point to the need for modeling techniques beyond that which current data models such as the relational and entity-relationship models provide.