Schema evolution

Abstract: As ontology development becomes a more ubiquitous and collaborative process, ontology versioning and evolution becomes an important area of ontology research. The many similarities between database-schema evolution and ontology evolution will allow us to build on the extensive research in schema evolution. However, there are also important differences between database schemas and ontologies. The differences stem from different usage paradigms, the presence of explicit semantics and different knowledge models. A lot of problems that existed only in theory in database research come to the forefront as practical problems in ontology evolution. These differences have important implications for the development of ontology-evolution frameworks: The traditional distinction between versioning and evolution is not applicable to ontologies. There are several dimensions along which compatibility between versions must be considered. The set of change operations for ontologies is different. We must develop automatic techniques for finding similarities and differences between versions.

Abstract: Schema Matching and Mapping provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed information systems requirements. Topics include effective methods for matching data, mapping transformation verification, mapping-driven schema evolution and merging.

Abstract: Advanced Database System by Carlo Zaniolo, Stefano Ceri, Christos Faloutsos, Richard T Snodgrass, VS Subrahmanian, and Roberto Zicari Preface 1 Introduction Part I Active Databases 2 Syntax and Semantics of Active Databases 21 Starburst 211 Syntax of the Starburst CREATE RULE Statement 212 Semantics of Active Rules in Starburst 213 Other Active Rule Commands 214 Examples of Active Rule Executions 22 Oracle 221 Syntax of the Oracle CREATE TRIGGER Statement 222 Semantics of Oracles Triggers 223 Example of Trigger Executions 23 DB2 231 Syntax of the DB2 CREATE TRIGGER Statement 232 Semantics of DB2 Triggers 233 Examples of Trigger Executions 24 Chimera 241 Summary of Chimera 242 Syntax of the Chimera Define Trigger Statement 243 Semantics of Chimera Triggers 244 Examples of Trigger Executions 25 Taxonomy of Active Database Concepts 26 Bibliographic Notes 27 Exercises 3 Applications of Active Databases 31 Integrity Management 311 Rule Generation 312 Example 32 Derived Data Maintenance 321 Rule Generation 322 Example 33 Replication 34 Workflow Management 35 Business Rules 351 A Case Study: Energy Management System (EMS) 352 Database Schema for the EMS Case Study 353 Business Rules for the EMS Case Study 36 Bibliographic Notes 37 Exercises 4 Design Principles for Active Rules 41 Properties of Active Rule Execution 411 Termination 412 Confluence 413 Observable Determinism 42 Rule Modularization 421 Behavioral Stratification 422 Assertional Stratification 423 Event-Based Stratification 43 Rule Debugging and Monitoring 44 IDEA Methodology 441 Active Rule Design 442 Active Rule Prototyping 443 Active Rule Implementation 444 Design Tools Supporting the IDEA Methodology 45 Summary and Open Problems 46 Bibliographic Notes 47 Exercises Part II Temporal Databases 5 Overview of Temporal Databases 51 A Case Study 511 Temporal Projection 512 Temporal Join 513 Summary 52 The Time Domain 53 Time Data Types 54 Associating Facts with Time 541 Dimensionality 542 Underlying Data Model 543 Representative Data Models 55 Temporal Query Languages 56 Summary 57 Bibliographic Notes 58 Exercises 6 TSQL2 61 Time Ontology 62 Data Model 63 Language Constructs 631 Schema Definition 632 The SELECT Statement 633 Restructuring 634 Partitioning 635 The VALID Clause 636 The Modification Statements 637 Event Relations 638 Transaction-Time Support 639 Aggregates 6310 Schema Evolution and Versioning 64 Other Constructs 65 Summary 66 Bibliographic Notes 67 Exercises 7 Implementation 71 System Architecture 72 Adding Temporal Support 721 DDL Compiler 722 Query Compiler 723 Run-Time Evaluator 73 Minimal support Needed for TSQL2 731 Data Dictionary and Data Files 732 DDL Compiler 733 Query Compiler 734 Run-Time Evaluator 735 Transaction and Data Manager 74 Summary and Open Problems 75 Bibliographic Notes 76 Exercises Part III Complex Queries and Reasoning 8 The Logic of Query Languages 81 Datalog 82 Relational Calculi 83 Relational Algebra 84 From Safe Datalog to Relational Algebra 841 Commercial Query Languages 85 Recursive Rules 86 Stratification 87 Expressive Power and Data Complexity 88 Syntax and Semantics of Datalog Languages 881 Syntax of First-Order Logic and Datalog 882 Semantics 883 Interpretations 89 The Models of a Program 810 Fixpoint-Based Semantics 8101 Operational Semantics: Powers of Tp 811 Bibliographic Notes 812 Exercises 9 Implementation of Rules and Recursion 91 Operational Semantics: Bottom-Up Execution 92 Stratified Programs and Iterated Fixpoint 93 Differential Fixpoint Computation 94 Top-Down Execution 941 Unification 942 SLD-Resolution 95 Rule-Rewriting Methods 951 Left-Linear and Right-Linear Recursion 952 Magic Sets Method 953 The Counting Method 954 Supplementary Magic Sets 96 Compilation and Optimization 961 Nonrecursive Programs 962 Recursive Predicates 963 Selecting a Method for Recursion 964 Optimization Strategies and Execution Plan 97 Recursive Queries in SQL 971 Implementation of Recursive SQL Queries 98 Bibliographic Notes 99 Exercises 10 Database Updates and Nonmonotonic Reasoning 101 Nonmonotonic Reasoning 102 Stratification and Well-Founded Methods 1021 Locally Stratified Programs 1022 Well-Founded Models 103 Datalog (1s) and Temporal Reasoning 104 XY-Stratification 105 Updates and Active Rules 106 Nondeterministic Reasoning 107 Research Directions 108 Bibliographic Notes 109 Exercises Part IV Spatial, Text, and Multimedia Databases 11 Traditional Indexing Methods 111 Secondary Keys 1111 Inverted Files 1112 Grid File 1113 k-D Trees 1114 Conclusions 112 Spatial Access Methods (SAMs) 1121 Space-Filling Curves 1122 R-Trees 1123 Transforming to Higher-D Points 1124 Conclusions 113 Text Retrieval 1131 Full Text Scanning 1132 Inversion 1133 Signature Files 1134 Vector Space Model and Clustering 1135 Conclusions 114 Summary and Future Research 115 Bibliographic Notes 116 Exercises 12 Multimedia Indexing 121 Basic Idea 122 GEMINI for Whole Match Queries 123 1-D Time Series 1231 Distance Function 1232 Feature Extraction and Lower-Bounding 1233 Introduction to DFT 1234 Energy-Concentrating Properties of DFT 1235 Experiments 124 2-D Color Images 1241 Image Features and Distance Functions 1242 Lower-Bounding 1243 Experiments and Conclusions 125 Subpattern Matching 1251 Sketch of the Approach-ST-Index 1252 Experiments 126 Summary and Future Research 127 Bibliographic Notes 128 Exercises Part V Uncertainty in Databases and Knowledge Bases 13 Models of Uncertainty 131 Introduction 1311 Uncertainty in DBs: An Image Database Example 1312 Uncertainty in DBs: A Temporal Database Example 1313 Uncertainty in DBs: A Null-Value Example 132 Models of Uncertainty 1321 Fuzzy Sets 1322 Lattice-Based Approaches 1323 Relationship to Fuzzy Logic 1324 Probability Theory 133 Bibliographic Notes 134 Exercises 14 Uncertainty in Relational Databases 141 Lattice-Based Relational Databases 1411 An Example 1412 Querying Lattice-Based Databases 142 Probabilistic Relational Databases 1421 Probabilistic Relations 1422 Annotated Relations 1423 Converting Probabilistic Tuples to Annotated Tuples 1424 Manipulating Annotated Relations 1425 Querying Probabilisitc Databases 143 Bibliographic Notes 144 A Final Note 145 Exercises 15 Including Uncertainty in Deductive Databases 151 Generalized Annotated Programs (GAPs) 1511 Lattice-Based KBs: Model Theory 1512 Lattice-Based KBs: Fixpoint Theory 1513 Lattice-Based KBs: Query Processing 152 Probabilisic Knowledge Bases 1521 Probabilistic KBs: Fixpoint Theory 1522 Probabilistic KBs: Model Theory 1523 Probabilistic KBs: Query Processing 153 Bibliographic Notes 154 Research Directions 155 Summary 156 Exercises Part VI Schema and Database Evolution in Object Database Systems 16 Object Databases and Change Management 161 Why Changes Are Needed 162 The Essence of Object Databases 1621 Basics of Object Databases 1622 Standards 1623 Change Management in Object Database Systems 163 Bibliographic Notes 164 Exercises 17 How to Change the Schema 171 Changing the Schema Using Primitives 1711 Taxonomy of Schema Modifications 1712 Schema Evolution Primitives in O2 172 Schema Invariants 173 Semantics of Schema Modifications 174 Bibliographic Notes 175 Exercises 18 How to Change the Database 181 Immediate vs Deferred Transformations 1811 Immediate Database Trasformation 1812 Deferred Database Transformation 182 Preserving Structural Consistency 1821 Structural Consistency Preserving Primitives 1822 Structural Consistency Modifying Primitives 183 User-Defined and Default Transformations 1831 Default Database Transformations 1832 User-Defined Database Transformations 1833 User-Defined Object Migration Functions 184 Implementing Database Updates in O2 1841 Problems with Deferred Database Transformations 1842 Data Structures 1843 the Deferred Database Update Algorithm 185 Related Work 186 Bibliographic Notes 187 Exercises 19 How to Change the Database Fast 191 Factors Influencing the Performance of a Database Transformation 1911 Immediate Database Tranformation 1912 Deferred Transformation 1913 Hybrid 192 How to Benchmark Database Updates 1921 Basic Benchmark Organization 1922 How to Run the Benchmark 193 Performance Evaluation 1931 Small Databases 1932 Large Databases 194 Open Problems 195 Bibliographic Notes Bibliography Author Index Subject Index

Abstract: Process-oriented support of collaborative work is an important challenge today. At first glance, Workflow Management Systems (WfMS) seem to be very suitable tools for realizing team-work processes. However, such processes have to be frequently adapted, e.g., due to process optimizations or when process goals change. Unfortunately, runtime adaptability still seems to be an unsolvable problem for almost all existing WfMS. Usually, process changes can be accomplished by modifying a corresponding (graphical) workflow (WF) schema. Especially for long-running processes, however, it is extremely important that such changes can be propagated to already running WF instances as well, but without causing inconsistencies and errors. The paper presents a general and comprehensive correctness criterion for ensuring compliance of in-progress WF instances with a modified WF schema. For different kinds of WF schema changes, it is precisely stated, which rules and which information are needed at mininum for satisfying this criterion.