时态变量"Now"语义及相应时态关系运算

讨论了时态变量"Now"的基本语义,即Now不仅可以表示当前时间,还能表示过去时间和将来时间.在语义分析的基础上,讨论了带变量时态关系运算中需要解决的基本问题,即变量Now值的确定问题,研究了相应时态关系数据操作,建立了带变量时态关系代数系统.     

模糊时态数据库关系代数演算规则分析

为了解决时态数据库对客观世界更符合实际抽象描述,能有效表示和处理复杂对象的模糊时态特性,从基本模糊时态数据模型入手,定义了一系列模糊时态关系操作元素,并论证了模糊时态区间关系代数的语法和语义,建立了一个能描述模糊时态信息的关系代数理论体系.避免了时态数据库不能提供表达模糊时态信息的环境设施,也增强了现有的时态数据库描述模糊事物特性的能力.     

时态面向对象数据库查询算法研究

时态关系数据库在关系数据库的基础上扩充了对时间数据的处理、而时态面向对象数据库则是在面向对象数据库的基础上扩充了对时间数据的处理。在时态数据基态修正模型的基础上,讨论了时态面向对象数据库查询优化策略,并给出相应的算法。     

嵌套的关系查询及优化

基于面向对象数据模型的查询同关系数据模型查询具有相似的特性和一些明显不同。这些差别表现在面向对象数据库查询、计值的复杂性和实施策略。论文提出一种嵌套的关系数据模型，并用来构造面向对象的数据模型。在此基础上研究了一种基于面向对象数据模型的查询模式，在等价的基础上给出了面向对象的查询与关系查询的转换方式。     

对象概念模式及其数据库技术研究

在 E- R分析、语义对象模型和关系数据库的基础上 ,主要结合面向对象方法和数据库特种技术以及笔者在数据库编程方面的实践经验 ,提出了数据库对象概念模式 ,讨论了其中的主要概念 ,并在此模式上重新定义或说明了一些重要的数据库操作 ,如对象集合、时态数据库、多维分析等等     

时态数据库的可视化方法与技术

1 引言时态数据库是将时间的概念结合到传统的数据库中。近十年来,人们对此所作的许多研究主要集中在把关系数据模型扩展为时态模型以及(或)把关系查询语言SQL和Quel扩展为时态的模式。除了强调关系模型之外,也有一些研究是将ER和其他的语义数据模型扩展到时态方面。时态数据模型的形式化和时态数据库的物理数据组织结构也受到了人们的关注。     

构建面向对象时态数据模型的研究

本文通过对现存关系数据库和面向对象数据库的比较分析，总结其优点与不足，并在结合了二者优点的UniSQL/X模型基地上，对该模型进行时态上的扩展，使它能够记录和处理时态信息。在查询代数中，引入了一 些特殊的时态操作，通过聚集、概括和时间参考三种关联对对象进行访问，而且此代数同时反映了时态关系代数和对象代数的特点。     

一种时态数据形式语言模型

数据模型是数据库技术发展的主线,时态数据模型是时态数据库系统的核心与基础。针对时态数据模型的研究现状,初步探讨了时态数据模型的基本要素,建立了一种形式化时态数据模型;基于形式语言理论和形式语义学的指称语义方法,进一步建立了该时态数据模型的形式语言模型。应用时态数据形式语言模型定义了各类时态完整性约束的形式语义规则,深入分析了时态数据模型内在的时态语义联系,为时态数据模型的研究提供了一个便利、高效的形式化理论框架。     

基于代数-时态逻辑的象形对象语义模型探讨

本文在“基于代数－时态逻辑的象形对象研究”一文的基础上，进一步讨论了“基于代数－时态逻辑的象形对象语义模型“问题，主要是将基于代数模型和基于时态逻辑模型这两种方法结合，通过OOCPN描述形式，对象形对象语义模型进行了探索式研究，具体包括象形对象标记，象形对象语义解释结构，象形对象语义结构模型结构，定义了状态运算符，操作运算符并给出其语义域上的解释，提出了可继承属性和可继承操作，完全继承和和部分继承等概念，并用来刻画象形对象系统中的类结构及继承性，在分类结构，组装结构的基础上提出了聚合类结构及分类－聚合类结构；给出了象形对象类类型的代规范描述，给出了有关象形对象系统的公理和定理；并用OOCPN（Object-Oriented Color Petri Net）对象形对象的继承性，类结构及类变化，重码语义的可能性和有害性等进行了描述。     

网络化自动测试系统的数据模型研究

依据网络化自动测试系统(NATS)存储和查询功能对数据模型的要求,比较扩展关系数据模型、语义数据模型和面向对象数据模型等多媒体数据模型实现方式的优缺点,提出数据库设计的基本框架为静态数据信息采用关系型数据模型,非结构化的多媒体数据信息采用对象-关系模型与文件系统结合的方式,并完成NATS的总体设计。实验结果证明了该框架的有效性。     

A Methodological Approach for Object-Relational Database Design using UML

The most common way of designing databases is by means of a conceptual model, such as E/R, without taking into account other views of the system. New object-oriented design languages, such as UML (Unified Modelling Language), allow the whole system, including the database schema, to be modelled in a uniform way. Moreover, as UML is an extendable language, it allows for any necessary introduction of new stereotypes for specific applications. Proposals exist to extend UML with stereotypes for database design but, unfortunately, they are focused on relational databases. However, new applications require complex objects to be represented in complex relationships, object-relational databases being more appropriate for these requirements. The framework of this paper is an Object-Relational Database Design Methodology, which defines new UML stereotypes for Object-Relational Database Design and proposes some guidelines to translate a UML conceptual schema into an object-relational schema. The guidelines are based on the SQL:1999 object-relational model and on Oracle8i as a product example. Initial submission: 22 January 2002 / Revised submission: 10 June 2002 Published online: 7 January 2003 This paper is a revised and extended version of Extending UML for Object-Relational Database Design, presented in the UML’2001 conference [17].     

Performance evaluation of the object-relational transformation methodology

The emergence of the object-oriented (OO) methodology has shown its capabilities in modelling the real world better than the earlier relational methodology. However, object-oriented databases (OODBs) are still considered immature in comparison with relational databases (RDBs) which have existed for many years. RDBs still continue to dominate the implementation of databases constituting more than 90% of all database implementations [28]. It was felt worthwhile to exploit the great modelling power of OO methodology, while still facilitating relational implementations. These reasons have led us to develop an object-relational transformation methodology [20, 21, 22, 23, 24 and 25] which allows us to use the OO methodology for data modelling and to transform it into a relational logical model for implementation in relational database management systems (RDBMSs). The main purpose of this paper is to present a performance evaluation of the transformation methodology. The evaluation covers I/O cost models of different types of queries. The type of evaluation is basically comparison-based, in which the performance of SQL operations upon a set of tables derived from the relational data model is compared with the tables derived from the OO data model using the transformation methodology. The results of the evaluation show that the performance of the RDB implementation transferred from an OO conceptual model using our object-relational transformation methodology is better than the relational implementation using a conventional relational modelling. Moreover, in many cases, the relational modelling is not applicable since it cannot capture the design semantics particularly relating to collection types. Our object-relational methodology solves this problem.     

Graph queries for data integration using xml

A new visual language, which is called ER-QBE and uses a conceptual model semantics, is proposed for the development of XML views. ER-QBE is based on graph queries that are trees of parametric SQL queries. The ER-QBE language is characterized by formally proved completeness, its expressiveness is higher than that of well-known alternatives, and it supports both relational and object-relational databases. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 171–183, March–April 2008.     

时态XML索引技术

首先通过讨论时态XML查询数据模型TXQDM,提出了基于结点有效时间的前缀编码方案.以此为基础,引入TXQDM结点间的基于时态连通的等价关系和基于时态包含的拟序关系,建立了时态XML索引数据模型TXIDM,该模型的基本特征是具有二重嵌套的索引框架,适合于TXQDM这种不规则的具有较大随意性的树形结构情形.其次,在TXIDM框架内,讨论了相应时态查询算法,其中包括基于时态的路径查询和值查询,同时,还讨论了时态索引更新算法,其中包括插入和修改算法.最后,对于文中提出的模型TXIDM和时态索引操作算法进行了性能分析且设计了相应模拟实验.实验结果表明,基于TXIDM的时态查询与更新算法是可行的和有效的.     

Bridging the gap between OWL and relational databases

Despite similarities between the Web Ontology Language (OWL) and schema languages traditionally used in relational databases, systems based on these languages exhibit quite different behavior in practice. The schema statements in relational databases are usually interpreted as integrity constraints and are used to check whether the data is structured according to the schema. OWL allows for axioms that resemble integrity constraints; however, these axioms are interpreted under the standard first-order semantics and not as checks. This often leads to confusion and is inappropriate in certain data-centric applications. To explain the source of this confusion, in this paper we compare OWL and relational databases w.r.t. their schema languages and basic computational problems. Based on this comparison, we extend OWL with integrity constraints that capture the intuition behind similar statements in relational databases. We show that, if the integrity constraints are satisfied, they need not be considered while answering a broad range of positive queries. Finally, we discuss several algorithms for checking integrity constraint satisfaction, each of which is suitable to different types of OWL knowledge bases.     

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.     

基于本体的关系数据集成的查询处理

为实现异构关系数据库的语义集成,针对传统集成技术存在的问题,在对语义网等相关技术进行分析的基础上,研究基于本体的关系数据集成系统中的查询处理问题,提出了一种基于本体的关系数据库集成框架。设计了基于本体的关系数据的描述方法,使用本体作为集成的全局模式来描述关系模式的语义。设计了查询重写算法,该算法可以将基于全局模式的SPARQL查询重写为针对具体关系数据库的查询,从而实现对异构关系数据库的集成。实验表明,该算法具有良好的可扩展性。     

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.     

Designing nesting structures of user-defined types in object-relational databases

This paper presents a methodology for designing proper nesting structures of user-defined types in object-relational databases. Briefly, we envision that users model a real-world application by using the EER model, which results in an EER schema. Our algorithm then uses the theory we developed for nested relations to generate scheme trees from the EER schema. We shall prove that the resulting scheme trees have exactly the same information content as the EER schema, and the scheme-tree instances over the resulting scheme trees do not store information redundantly. Finally, the scheme trees are transformed to Oracle Database 10g nested object types for implementation. The algorithm in this paper forms the core of a computerized object-relational database design tool we shall develop in the future.     

全要素模型与关系模型的关系解析映射

为实现基于全要素模型的空间信息关系数据库存储,首先对全要素模型(FullFeatureModel,FFM)及其关系类型进行了分析,阐述了FFM与关系模型映射的内容;然后提出了一种FFM与关系模型的关系解析映射方法,给出了基于图论的具体映射过程与算法;最后实现了表达FFM的复杂图与关系模式之间的转换,并给出了具体实例;为空间信息基于关系数据库的集成与共享等奠定了基础。