A conceptual model for the logical design of temporal databases

Although widely advocated as a tool for the conceptual modelling of data, the Entity-Relationship (E-R) model [4] and its extensions are generally lacking in constructs to model the dynamic nature of the real world, making them inadequate for designing temporal databases. This research first extends the E-R model to a Temporal Event-Entity-Relationship Model (TEERM), by introducing events as an additional construct. Second, a method is proposed for mapping this conceptual model into a temporal relational model for the logical design of temporal relational databases with a corresponding set of integrity constraints. The model is illustrated with an example and evaluated using a set of criteria proposed by ^{Batini et al. [2]}. The model appears to be expressive, simple and easy to use, and should, therefore, aid the temporal database design process significantly.     

Implementation design for databases: the `forgotten' step

Most methodologies for database analysis and design specify conceptual, logical, and physical design as the three major design steps. However, although this three-step approach is popular, there is no consensus on when to use implementation design techniques, such as table partitioning and denormalization. Consequently, these techniques are treated as substeps in one of the three main design steps. This inconsistent treatment may be why many designers frequently rely on their intuition in applying implementation design techniques. Clearly, this ad hoc practice shouldn't continue. Ad hoc anything is not a good idea when designing a complex system. To resolve this problem, the author proposes that we extend the three-step methodology to include a fourth major step: implementation design. In this methodology, implementation design is the process of modifying an “ideal” logical data model (relational or object-oriented) to produce a more machine-efficient, “pragmatic” model: the implementation model. The implementation model, in turn, serves as input to the physical design step. This four-step method will encourage practitioners to resist the ad hoc approach and simplify the other design steps. It will also help in addressing the additional complexity associated with advanced database architectures, such as distributed and parallel databases and data warehouses     

数据库设计工具集DBTOOLS的设计

本文介绍的数据库设计工具集DBTOOLS包括扩充的E—R模型设计工具EERD、从E—R模型到关系模型转换工具ERTR、从DFD、DD到关系模型转换工具DDTR,DBTOOLS以自动转换和人工干预相结合的方式工作,提供对关系数据库概念结构设计和逻辑结构设计的支持,DBTOOLS的设计中强调语义信息的描述和运用,以及对数据库应用系统增量开发的支持。     

A survey of database design transformations based on the Entity-Relationship model

At present, the Entity-Relationship (ER) model is the most important paradigm for conceptual database design. Since the model was introduced in the mid-seventies, a large body of literature has been published on transforming conceptual ER schemas or diagrams into logical data models. The purpose of this paper is to survey this literature. A first focus is on transformation approaches from the ER model to traditional data models, i.e. to the relational, the network, or the hierarchical model; this is then complemented by a discussion of more recent transformations to object-oriented models. A second focus is on considering the process of reverse engineering, i.e. transformations from a logical model back into the ER model; finally, an overview of direct transformations between various logical data models is presented.     

Conceptual design of fuzzy object-oriented databases using extended entity-relationship model

Entity-relationship–extended entity-relationship models play a crucial role in the conceptual design of relational databases as well as object-oriented databases. Recently, several approaches have been proposed to enhance object-oriented databases (OODBs) using fuzzy set theory. In this paper, we introduce a fuzzy extended entity-relationship model to cope with imperfect as well as complex objects in the real world at a conceptual level. In particular, we provide the formal approach to mapping a fuzzy extended entity-relationship model to a fuzzy object-oriented database schema. © 2001 John Wiley & Sons, Inc.     

Novice errors in conceptual database design

Conceptual and logical database modelling are difficult tasks for designers, and the potential for committing and correcting errors is significant. This paper reports on two laboratory experiments that investigated the underlying causes of errors committed by novice designers engaged in conceptual database modelling tasks. These causes can be traced to combinatorial complexity of the task, biases resulting from misapplication of heuristics, and incomplete knowledge about database design. The most common error was that subjects translated their initial understanding of the application into final database structures and did not consider alternative hypotheses and solutions. The paper includes recommendations to reduce the occurrence of errors.     

Translational Semantics for a Conceptual Level Query Language

A conceptual level database language for the entity relationship (ER) model implicitly contains integrities basic to ER concepts and special retrieval semantics for inheritances of attributes and relationships.Prolog,which belongs to the logical and physical level,cannot be used as a foundation to directly define the database language.It is shown how Prolog can be enhanced to understand the concepts of entities,relationships,attributes and is-a relationships.The enhanced Prolog is then used as a foundation to define the semantics of a database query language for the ER model.The three basic functions of model specification,updates and retrievals are defined.     

Complete rules for n-ary relationship cardinality constraints

An extended approach is presented for modeling data relationships that involve multiple entities. This approach unifies the relationship cardinality constraints defined by a variety of existing approaches into a common framework and extends the types of constraints captured. A concise tabular notation for specifying such constraints is introduced. The result is a modeling technique that captures more completely the nature of data relationships. Rules are defined for identifying inconsistencies among cardinality constraints specified for a given data relationship. Specific subsets of these rules are shown to be complete for four of the most commonly used variations of cardinality constraints. These rules extend work done in axiomatization of functional and numerical dependencies for relational databases into the area of conceptual data models.     

Handling complex and uncertain information in the ExIFO andNF2 data models

Trends in databases leading to complex objects present opportunities for representing imprecision and uncertainty that were difficult to integrate cohesively in simpler database models. In fact, one can begin at the conceptual level with a model that allows uncertainty assumptions and then transform those assumptions into a logical model having the necessary semantic foundations upon which to base a meaningful query language. Here we provide such a constructive approach beginning with the ExIFO model for expression of the conceptual design then show how the conceptual design is transformed into the logical design (for which we utilize the extended NF² logical database model). The steps are straightforward, unambiguous, and preserve the relevant information, including information concerning uncertainty     

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.     

一种基于最大加权频繁项目集的数据库相似性判别算法

在引入最大加权频繁项目集之后，给出一种新的数据库相似性度量模型，并提出基于最大加权频繁项目集的数据库相似性度量算法．该算法可有效地改进基于最大频繁项目集的数据库相似性度量方法，提高数据库相似性度量准确性．在实际应用中，改进模型为分布多库环境下数据挖掘的数据准备提供有效的框架，因而具有重要的使用价值．     

An automated entity–relationship clustering algorithm for conceptual database design

Entity–relationship (ER) modeling is a widely accepted technique for conceptual database design. However, the complexities inherent in large ER diagrams have restricted the effectiveness of their use in practice. It is often difficult for end-users, or even for well-trained database engineers and designers, to fully understand and properly manage large ER diagrams. Hence, to improve their understandability and manageability, large ER diagrams need to be decomposed into smaller modules by clustering closely related entities and relationships. Previous researchers have proposed many manual and semi-automatic approaches for such clustering. However, most of them call for intuitive and subjective judgment from “experts” at various stages of their implementation. We present a fully automated algorithm that eliminates the need for subjective human judgment. In addition to improving their understandability and manageability, an automated algorithm facilitates the re-clustering of ER diagrams as they undergo many changes during their design, development, and maintenance phases.     

Multiversion object constellations: A new approach to support a designer's database work

The logical organization of database support for CAD applications is considered, which has to account for specific requirements including versioning, consistency and design transactions. A new approach to the organization, manipulation and management of design objects in a design database is described, which is based on the notion of an objectconstellation. A constellation is a set of multiversion objects together with all their subobjects. Constellations can be versioned intoconfigurations, which comprise one version of each object of the underlying constellation. We argue that constellations are adequate units of allocation to individual designers, while configurations form appropriate units of consistency. We show how the constellation approach renders a flexible support of hierarchically organized, cooperative design processes possible, by employing specific transactions whose scope is limited to well-defined portions of a database. Most importantly, the approach provides new insight into the consistency problem for design databases, by providing an adequate approach to multilevel consistency, and by making consistency of a design context-dependent.     

Enriching the ER model based on discovered association rules

The entity-relationship (ER) model, a powerful means for business and data modeling, needs to be enriched with new semantics as the real world changes and its understanding improves. This paper attempts at enriching the ER model based on association rules (AR) discovered from large databases by introducing specializations and sub-types into the ER model. The proposed framework is extended to deal with more general, flexible and linguistic knowledge in fuzzy association rules. Moreover, transforming an AR-enriched-ER (AR-EER) schema to a relational database (RDB) schema is also investigated.     

Using an entity model to drive physical database design

Logical relational database design, because of its implementation-independent nature, has been successfully formalized. Physical relational database design, because of its implementation-dependent nature, has remained largely unformalized and disconnected, not only from logical design but also from conceptual database design. The paper suggests a model for the physical design process that has proven useful in a number of practical development projects. The model demonstrates that a seamless join between conceptual, logical and physical design work is feasible. It illustrates how the process of annotating a conceptual model with physical detail provides a useful framework for driving the process of physical relational database design.     

数据库逻辑设计中消除规范化处理问题

关系数据库设计要求规范化处理的过程以消除数据冗余和更新异常问题. 范式化理论的算法与数据依赖有着直接的联系, 数据依赖中最重要的是函数依赖, 识别该依赖既耗时又复杂. 讨论如何在采用ER模型的数据库逻辑设计步骤中消除规范化处理过程, 在概念结构设计过程中遵循一组规则将产生满足3NF范式的初始关系模式集, 以节省数据库设计者在导出初始关系模式集后的规范化处理步骤.     

关系数据库与面向对象数据库的集成

本文从ＲＤＢ（ｒｅｌａｔｉｏｎａｌｄａｔａｂａｓｅ）的缺欠、ＯＯＤＢ（ｏｂｊｅｃｔｏｒｉｅｎｔｅｄｄａｔａｂａｓｅ）的不足和新的数据库应用需求３个方面指出了统一关系范型和ＯＯ范型、集成ＲＤＢ与ＯＯＤＢ的趋势，讨论了集成ＲＤＢ与ＯＯＤＢ的３种途径，最后介绍了一个集成关系与对象模型的多媒体数据库系统ＴＨＣＩＭＨＹＰＥＲ的总体设计.     

面向机械产品概念设计的知识库设计研究

针对机械产品概念设计中设计知识功能语义定义模糊和隐形知识重用率低的问题, 研究了基于领域本体表示的知识库设计方法,支持设计知识的自助发布管理和语义信息检索等 功能。提出设计知识表示的本体模式和建模方法,建立领域本体;从概念设计方案需求粒度、 功能目标及企业知识自管理等方面考虑,建立多维设计知识分类体系;设计JSON 文件到OWL 文件的映射规则,实现设计知识的发布、维护、存储和检索。最终实现面向机械产品概念设计 的知识管理,为企业设计人员提供知识共享和重用,支持产品概念设计的方案创新。     

Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.