时态信息处理技术及应用

章节摘录

　　Abstract Time data is one of the basic data types in database systems. There are two modes of using time data in applications， one is the explicit mode and the other is the implicit mode. In the second mode of application， time attributes of information need to be handled. In this chapter， we introduce three basic types of time data， i.e.， point， interval and span. Subsequently， we propose the concepts of temporal information， temporal database and temporal systems， and introduce the basic concepts and core technologies of temporal database. We also analyze the origin and development of temporal information processing technologies and divide the evolution in this research field into three phases. Finally， we analyze the current situation in temporal research field and propose some trends of temporal information technologies.　　Keywords time data， temporal information， temporal database， temporal system， basic concept， evolution， trends　　1.1 Application Requirement　　Time exists everywhere in the world. Its attributes are applied in many areas， such as e-commerce， e-government， global information system， and the stock market. However， some applications process time attribute in the same way as they would process a common attribute. For example， web sites can record logon time of users， but simply regard them as a normal attribute like number or character data type. We call these temporal applications implicit applications. There are other temporal applications that require special time processing mechanisms to manage time attributes. We call these applications explicit applications.

前言

　　Time is a natural attribute of everything. With the explosive growth of computerand network systems， temporal information has received extensive attention inboth academia and industry. It plays an increasingly important role in the newgeneration information systems and also a key role in some applications. The useof temporal information modeling and processing technology in these applicationscan make them more useful and more convenient.　　Temporal database and application problems have been mentioned during the1970s. The groundbreaking study in this area was conducted by J. Ben Zvi， whoproposed the bitemporal concept and a temporal database model in his dissertation，submitted to the University of California， Los Angeles， in 1982. In subsequentyears， the temporal database theory research has grown vigorously and hundredsof temporal models have been proposed. James Clifford， Christian S. Jensen，Richard T. Snodgrass and Andreas Steiner made important contributions to temporaldatabase models， theory and technology. In the recent years， along with informationtechnology that can meet the increasing requirement for new applications， thetemporal database theory and application technologies have made remarkableprogress. However， there are many problems in temporal information processing，e.g.， weakness in temporal calculus theory， low efficiency of temporal storageand access， complex temporal information processing and lack of the softwaredevelopment tools. There are three main trends in temporal technologies： modelstandardization， middleware development and application diversification.　　We began to pay special attention to research on temporal database when weundertook the software application project： Intelligent Decision Support Systemof Salary （SIDSS）， in 1998. The main concept behind SIDSS is that an employeeswage is paid according to information related to the employee and to the policiesof the salary management department. SIDSS is a typical temporal system， inwhich the employee information that influences his or her salary is the typicaltemporal data and the salary policies that can be changed by the managementdepartment which also are time-varying knowledge.

书籍目录

PrefaceList of Figures and TablesPart I  Temporal Models and Calculation Methods1  From Time Data to Temporal Information  1.1  Application Requirement  1.2  What Is Time Data    1.2.1  Time Point    1.2.2  Time Interval    1.2.3  Time Span    1.2.4  Complex Time Data  1.3  Temporal Information, Temporal Database and Temporal System    1.3.1  What Is Temporal Information    1.3.2  Temporal Database    1.3.3  Temporal System  1.4  Origin and Development of Temporal Information Technologies    1.4.1  Founding Phase    1.4.2  Development Phase    1.4.3  Application Phase  1.5  Current Situation, Problems and Trends    1.5.1  Current Situation    1.5.2  Existent Problems in Temporal Database Research    1.5.3  Trends  References2  Time Calculation and Temporal Logic Method  2.1  Time Model    2.1.1  Continuous Model    2.1.2  Stepwise Model    2.1.3  Discrete Model    2.1.4  Non Temporal Model  2.2  Properties of Time Structure    2.2.1  Order Relations of Time Sets    2.2.2  First Order Properties of Time Flow  2.3  Point-Based Temporal Logic    2.3.1  Temporal Extensions Based Snapshot Model    2.3.2  Temporal Extensions Based Timestamp Model  2.4  Interval-Based Temporal Logic    2.4.1  From Interval to Point    2.4.2  From Point to Point    2.4.3  Temporal Predict  2.5  Calculation Based on Span  2.6  Other Temporal Calculations in Common Use  2.7  Time Granularity andConversion Calculation    2.7.1  Time Granularity and Chronon    2.7.2  State of Existence of Time Granularity    2.7.3  Operations of Time Granularity    2.7.4  Relational Chart of Time Granularity Conversion  2.8  Tense Logic    2.8.1  Syntax and Semantics of Tense Logic    2.8.2  Axiomatics and Properties  References3  Temporal Extension of Relational Algebra  3.1  Regular Relational Operations    3.1.1  Basic Notions    3.1.2  Relational Algebra    3.1.3  Relational Calculus  3.2  Relational Algebra of Historical Database    3.2.1  Basic Notions and Terminologies    3.2.2  HRDM Model    3.2.3  Historical Relational Algebra of HRDM  3.3  Bitemporal Relational Algebra of BCDM    3.3.1  Basic Notions and Terminologies    3.3.2  Bitemporal Relational Algebra  3.4  Snapshot Reducibility and Temporal Completeness    3.4.1  Snapshot Reducibility    3.4.2  Temporal Semi-Completeness    3.4.3  Temporal Completeness   ReferencesPart II  Database Based on Temporal Information4  Temporal Data Model and Temporal Database Systems  4.1  Time-Dimensions    4.1.1  User-Defined Time    4.1.2  Valid Time    4.1.3  Transaction Time    4.1.4  Two Temporal Variables: Now and UC    4.1.5  An Illustration  4.2  Temporal Database Types    4.2.1  Snapshot Database    4.2.2  Historical Database    4.2.3  Rollback Database    4.2.4  Bitemporal Database  4.3  Temporal Data Models    4.3.1  Bitemporal Time Stamps    4.3.2  BCDM    4.3.3  Temporal Entity-Relationship Data Model  4.4  Difference from Real-Time Database  References5  Spatio-Temporal Data Model and Spatio-Temporal Databases  5.1  Introduction  5.2  Spatio-Temporal Data Model    5.2.1  Spatio-Temporal Object    5.2.2  Basic Considerations of Spatio-Temporal Modeling    5.2.3  Version Based Data Model    5.2.4  Event-Based Data Model    5.2.5  Constraint-Based Data Model    5.2.6  Moving Objects Data Model  5.3  Query on Spatio-Temporal Data    5.3.1  Spatio-Temporal Data Query    5.3.2  Moving Data Query    5.3.3  Spatio-Temporal Database Language  5.4  Structure of Spatio-Temporal Database System    5.4.1  Structure of Complete Type    5.4.2  Structure of Layered Type    5.4.3  Structure of Extended Type  Reference6  Temporal Extension of XML Data Model  6.1  Motivation    6.1.1  XML Temporal Driven    6.1.2  Commercial-Driven Temporal Database  6.2  Temporal Research of the Semi-Structured Data  6.3  Temporal XML Model and Query Mechanism  References7  Data Operations Based on Temporal Variables  7.1  Introduction  7.2  Data Model Based on Temporal Variables    7.2.1  Order and Temporal Variables    7.2.2  Main Body Instances    7.2.3  Bitemporal Relation Model Based on Variables  7.3  Data Updating    7.3.1  Data Inserting    7.3.2 Data Deleting    7.3.3  Data Modifying  7.4  Data Querying    7.4.1  Now in Current Versions    7.4.2  Now in Non-Current Version    7.4.3  Temporal Querying Algorithms   ReferencesPart III  Temporal Index Technologies8  Temporal Indexes Supporting Valid Time  8.1  Introduction  8.2  Summary of Temporal Index    8.2.1  Temporal Index Based on Transaction Time    8.2.2  Index Based on Valid Time    8.2.3  Bitemporal Index  8.3  TRdim    8.3.1  Relative Temporal Data Model    8.3.2  Temporal Relation Index Model  8.4  Data Querying and Index Updating    8.4.1  Index Querying    8.4.2  Index Updating   8.5  Simulation    8.5.1  Index Constructing    8.5.2  Query Based on Probability    8.5.3  Query Based on the Number of Data   References9  Indexes for Moving-Objects Data  9.1  Introduction  9.2  Data Model for Moving Objects    9.2.1  Data Model Modm    9.2.2  Temporal Summary  9.3  Index for Moving Object Data    9.3.1  Linear Order Division    9.3.2  Index Model Modim  9.4 Data Query  9.5  Index Update  References10  Temporal XML Index Schema  10.1  Introduction  10.2  Linear-Order Relation    10.2.1  Linear-Order Matrix    10.2.2  Linear-Order Equivalence Relation  10.3  Temporal Summary and Temporal Indexing    10.3.1  Data Model    10.3.2  Temporal Summary    10.3.3  Temporal Indexing  10.4  Data Query    10.4.1  Query Based onAbsolute Paths    10.4.2  Query Based on Relative Paths  10.5  Simulation and Evaluation    10.5.1  Environment and Data Design    10.5.2  Simulation and Evaluation  ReferencesPart 1V  Temporal Database Management Systems11  Implementation of Temporal Database Management Systems  11.1  Introduction  11.2  TimeDB    11.2.1  Installation    11.2.2  TimeDB 2.0 Beta 4's User Interface    11.2.3  Examples  11.3  TempDB    11.3.1  Installation    11.3.2  TempDB's User Interface    11.3.3  Examples  11.4  Comparing TimeDB with TempDB  References12  Improvement and Extension to ATSQL2  12.1  Introduction  12.2  Study on ATSQL2    12.2.1  Requirements and Expatiation    12.2.2  Properties of ATSQL2    12.3  Interpretation of ATSQL2 Semantics    12.3.1  Data Definition Statement    12.3.2  Data Manipulation Statement    12.3.3  Data Query Statement  12.4  Improved ATSQL2    12.4.1  Clear Regulation to the Semantic Operator    12.4.2  Re-Definition of Scalar Expression    12.4.3  Clearly Regulate the Usage of Common Operators and Temporal Operators in Conditional Statements  References13  Design and Implementation of TempDB  13.1  Introduction  13.2  Framework of TempDB    13.2.1  Middleware Architecture    13.2.2  Platform of Implementation    13.2.3  Architecture of TempDB  13.3  Implementation of TempDB    13.3.1  Temporal DDL    13.3.2  Temporal DML    13.3.3  Temporal Query  13.4  Processing Mechanism of Temporal Integrity Constraints    13.4.1  Basic Concepts    13.4.2  Temporal Insertion    13.4.3  Temporal Deletion    13.4.4  Temporal Modification  13.5  Optimization of Performance    13.5.1  Temporal Indexes and MAP21    13.5.2  Binding on Now    13.5.3  MAP21-B   ReferencesPart V  TemporalApplication and Case Study14  Research on Temporal Extended Role Hierarchy  14.1  Introduction  14.2  Related Work  14.3  Extended Role Hierarchy  14.4  Temporal Role Hierarchy    14.4.1  Time Constraint on the Inheritance of Restricted Special Permission    14.4.2  Temporal Inheritance Character    14.4.3  Space and Time Efficiency Analysis  References15  Temporal Workflow Modeling and Its Application  15.1  Introduction  15.2  Related Work  15.3  A Modified Workflow Meta-Model and Temporal Attributes    15.3.1  Build-Time Meta-Model    15.3.2  Run-Time Meta-Model    15.3.3  A Formal Model of Temporal Workflow  15.4  Fuzzy Temporal Workflow Nets (FTWF-Nets)    15.4.1  Fuzzy Time Point    15.4.2  Formal Definition for FTWF-Nets    15.4.3  Time Related Calculation in FTWF-Nets  15.5  Time Modeling and Time Possibility Analysis  15.6  An Illustration  References16  Temporal Knowledge Representation and Reasoning  16.1  Introduction  16.2  Temporal Production System     16.2.1  Basic Definitions    16.2.2  Temporal Reasoning  16.3  Prototype Implementation in a Salary System    16.3.1  Global Database    16.3.2  Data Structures of Temporal Production Rules in Database    16.3.3  Data Structures of Facts in Database    16.3.4  Details in Reasoning    16.3.5  Binding Semantics of Now Variable  References17  Temporal Application Modes and Case Study  17.1  Temporal Application Modes    17.1.1  Entire Temporal Application Mode    17.1.2  Embedding Temporal Application Mode    17.1.3  Mix Temporal Application Mode  17.2  Temporal Data/Knowledge View    17.2.1  Temporal Data View    17.2.2  Temporal Data/Knowledge Model    17.2.3  Links of Temporal Knowledge and Temporal Data  17.3  Temporal Application in Cooperative Software    17.3.1  Three Basic Elements of Cooperative Software    17.3.2  Temporal Relation of Collaborative Roles    17.3.3  Temporal Extension in the Collaboration Information    17.3.4  Temporal Extension of Workflow    17.3.5  Case Study  17.4  SIDSS: A Typical Example of Temporal Application    17.4.1  Introduction    17.4.2  Temporal Data in SIDSS    17.4.3  Temporal Knowledge in SIDSS    17.4.4  Implementation of SIDSS  ReferencesAppendix   A.1  Extension ATSQL of TempDB 2.1   A.2  API of TempDB 2.1Index

作者简介

《时态信息处理技术及应用》读者对象为高等院校计算机专业的师生，科研机构及相关领域的研发人员等。时间是自然界无处不在的属性。时态信息处理已经成为现代信息系统的重要组成部分。《时态信息处理技术及应用》系统研究时态信息处理技术及其应用，内容包括：（1）时间模型、时间演算和时态逻辑方法；（2）时态数据库基本概念、时态数据模型、时间算子now的语义和时态数据索引；（3）时态数据查询语言，以TempDB为例介绍时态数据库管理系统的设计和实现；（4）XML、工作流时态扩展和时态知识模型；（5）时态应用模式，并给出一个典型的时态应用实例。

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