Conceptual Modeling of Information Systems

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Springer Science & Business Media, Aug 15, 2007 - Computers - 455 pages
It is now more than fifty years since the first paper on formal specifications of an information system was published by Young and Kent. Even if the term “conceptual model” was not used at that time, the basic intention of the abstract specification was to a large extent the same as for developing conceptual models today: to arrive at a precise, abstract, and hardware - dependent model of the informational and time characteristics of a data processing problem. The abstract notation should enable the analyst to - ganize the problem around any piece of hardware. In other words, the p- pose of an abstract specification was for it to be used as an invariant basis for designing different alternative implementations, perhaps even using different hardware components. Research and practice of abstract modeling of information systems has since the late fifties progressed through many milestones and achie- ments. In the sixties, pioneering work was carried out by the CODASYL Development committee who in 1962 presented the “Information Al- bra”. At about the same time Börje Langefors published his elementary message and e-file approach to specification of information systems. The next decade, the seventies, was characterized by the introduction of a large number of new types of, as they were called, “data models”. We saw the birth of, for instance, Binary Data Models, Entity Relationship Models, Relational Data Models, Semantic Data Models, and Temporal Deductive Models.
 

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Contents

Introduction
1
111 The Memory Function
3
112 The Informative Function
4
113 The Active Function
6
114 Examples of Information Systems
7
12 Conceptual Modeling
9
121 The Structural Schema
10
122 The Information Base
14
96 Bibliographical Notes
206
97 Exercises
208
Taxonomies
212
1011 The IsA Relationship
214
1012 Entity Types Derived by Intersection and Multiple Classification
215
1013 The Entity Type Entity
216
1021 The Gens Relationship
217
1022 Constraints on Generalizations
218

123 The Behavioral Schema
15
124 Integrity Constraints
18
125 Derivation Rules
20
126 The Principle of Necessity for Conceptual Schemas
21
13 The Abstract Architecture of an Information System
22
14 Requirements Engineering
27
15 Quality of Conceptual Schemas
28
16 A Brief History of Conceptual Modeling
31
162 Semantic Data Models
32
163 Conceptual Models of Information Systems
33
164 Object Orientation
34
Entity Types
37
211 Definitional Concepts
38
212 Functions of a Concept
39
214 ExemplarBased Concepts
40
23 Definition of Entity Types
41
231 Names
44
233 Subsumption
45
241 State of the Information Base
47
242 Logical Representation
48
243 Representation in UML
49
Single or Multiple Classification
50
Static or Dynamic Classification
51
25 Data Types
54
251 Data Types in UML
56
27 Exercises
58
Relationship Types
59
311 Degree
63
313 Unary Relationship Types
66
315 Subsumption
68
321 State of the Information Base
69
323 Representation in UML
70
324 Properties of the Representation
74
33 Attributes
75
331 Conceptual Models Based on Attributes
76
332 Attribute Pattern Sentence
77
334 On the Use of Attributes
78
34 Bibliographical Notes
80
35 Exercises
81
Cardinality Constraints
83
411 Existence Dependency Relationship Types
86
412 Recursive Relationship Types
87
413 Satisfiability of Cardinality Constraints
88
42 Cardinality Constraints of nary Relationship Types
90
421 Consistency and Inference Rules
93
43 Maximal Participation
95
44 Bibliographical Notes
98
45 Exercises
99
Particular Kinds of Relationship Type
103
511 Simple Reference
104
512 Compound Reference
105
513 Set Reference
106
52 Identification
107
521 Identifiability of Entity Types
109
54 Elementary Relationship Types
111
55 Decomposing NonElementary Relationship Types
113
551 Decomposition Based on Functional Dependencies
114
552 Decomposition Based on Multivalued Dependencies
116
553 Decomposition by Absorbing a Constant Entity Type
119
56 Bibliographical Notes
120
57 Exercises
121
Reification
123
62 Representation in UML
126
622 Implicit Reification
127
623 Implicit Reification as a Schema Transformation
129
63 Partial Reification
130
64 Bibliographical Notes
133
65 Exercises
134
Generic Relationship Types
137
72 Representation in an Information System
139
722 Representation in UML
140
73 PartWhole Relationships
141
732 Representation in UML
142
733 Part Sharing
143
734 Part Dependency
144
74 Grouping
145
742 Representation in UML
146
743 Homogeneous Versus Heterogeneous Groups
147
752 Representation in UML
149
753 Propagation
150
76 Materialization
151
762 Representation in UML
152
763 Inheritance
153
78 Exercises
155
Derived Types
157
812 Derived Types
158
813 Hybrid Types
159
815 Design of Derivability
160
82 Representation in an Information System
161
822 Representation in UML
162
823 Representation of Derivation Rules by Operations
164
83 Particular Kinds of Derived Type
167
832 Derived by Specialization
169
833 Derived by Exclusion
170
834 Derived by Participation
171
835 Transitive Closure
173
85 Hybrid Types in UML
175
86 Justification for Derived Types
176
87 Bibliographical Notes
178
88 Exercises
179
Integrity Constraints
181
912 Integrity Constraints
182
913 Violation of Integrity Constraints
183
914 Violation Response Actions
185
921 Classification According to Source
186
922 Classification According to Scope
187
923 Classification According to Cause of Violation
188
93 Representation in an Information System
189
932 Representation in UML
192
933 Representation of Constraints by Operations
193
94 Particular Kinds of Static Constraint
196
942 Reference Constraints
197
943 Inclusion Constraints
198
944 Disjunction Constraints
199
945 Covering Constraints
201
946 Constraints of Recursive Binary Relationship Types
202
947 Entity Type Cardinality Constraints
204
1023 GeneralizationSpecialization Dimension
220
1024 Explicit Subtypes versus Explicit Dimension Attributes
221
1025 Partitions
222
1031 Valid Type Configurations
223
1032 Taxonomic Constraints and Derivability
224
1033 Partitions and Derivability
227
104 Relationship Type Refinement
229
1042 Particular Kinds of Participant Refinement
232
1043 Cardinality Constraint Strengthening
233
1044 Interaction of IsA and Cardinality Constraints
236
1046 Redefining a Base Relationship Type as Derived
238
105 Constraint Specialization
239
106 SpecializationGeneralization of Relationship Types
241
1062 Reification and Specialization
242
107 Bibliographical Notes
243
108 Exercises
244
Domain Events
247
111 Domain Events as Sets of Structural Events
248
1112 Domain Events
251
112 Representation in an Information System
252
1122 Logical Representation
255
1123 UML Representation
256
113 Domain Event Constraints
257
1131 Logical Representation
258
The Postcondition Approach
260
1141 Logical Representation
261
1142 UML Representation
262
1143 The Frame Problem
265
The Procedural Approach
266
1151 Logical Representation
267
1152 UML Representation
268
116 Consistency with the Structural Schema
271
117 Bibliographical Notes
272
118 Exercises
274
Action Request Events
276
1211 Scope of this Chapter
281
1221 Characteristics of Action Request Events
283
1222 Constraints of Action Request Events
284
123 Effects of Queries
285
124 Effects of Action Request Events
289
1241 Effects of Domain Event Notifications
294
125 Event Specialization
295
126 Generating Conditions
296
127 Bibliographical Notes
297
State Transition Diagrams
299
1311 Finite Automata
300
132 Entities as State Machines
301
1321 Entity Life Cycle
305
133 State Transition Diagrams in UML
306
1331 Transitions Triggered by Change and Time Events
310
1332 UnexpectedEvent Reception
311
1334 Final State
312
1336 Choice
314
134 From Domain and Action Request Events to Call Events
315
1341 Localization of Event Constraints and Effects
317
135 Entity Types with Multiple State Transition Diagrams
321
136 Bibliographical Notes
322
137 Exercises
323
Statecharts
325
1411 Simple Composite States
327
1413 Initial Pseudostate
328
1414 Conflicting Transitions
329
1421 Initial Pseudostate
331
1422 Firing Multiple Transitions
332
1424 Join
333
144 Exercises
334
Use Cases
336
152 Use Cases
338
1522 Use Case Actors
339
1523 Use Case Specification
340
1524 Relationships Between Use Cases
343
1525 Use Case Model
345
153 Mapping Use Cases to Requests
346
1531 Textual References
347
1532 Creation Dependencies
348
154 Bibliographical Notes
350
Case Study
353
161 Main Domain Concepts
354
1622 Minimum Values
358
163 Store Administration
359
1632 Categories
363
1633 Products
366
164 Customers
370
165 Online Catalog
373
1652 Orders
376
1653 Show Previous Orders
380
Metamodeling
382
1712 Classification Level
385
1713 InstanceOf versus IsA
387
1714 Monolevel and Multilevel Information Bases
389
1715 Logical Representation
391
1716 Representation in UML
393
173 Class Relationship Types
394
174 Meta Relationship Types
397
1742 Logical Representation
398
1743 Representation in UML
399
175 Metaschemas
400
1752 Example of a Metaschema
401
1753 Levels of a Meta Information Base
405
1755 Conceptual Models versus Metaschemas
406
176 Stereotypes
408
1762 Stereotypes in the Metaschema
410
177 Bibliographical Notes
412
178 Exercises
413
The MOF and XMI
415
1812 The MOF
417
182 The MOF as a Conceptual Modeling Language
420
1821 The MOF as an ωmetaschema
421
183 XMI
422
1831 XMI Representation of Entities and Relationships
423
1832 XMI Representation of UML Schemas
425
184 Bibliographical Notes
428
185 Exercises
429
References
431
Index
445
Copyright

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About the author (2007)

Antoni Olivé is a professor of information systems at the Universitat Politčcnica de Catalunya in Barcelona. He has worked in this field during over 25 years. His main interests have been, and are, conceptual modeling, requirements engineering, information systems design and databases.

Antoni Olivé was the recipient of the DKE-ER Elsevier award for his contribution to the Intl. Conf. on Conceptual Modeling (ER'2003) and was Program Co-chair of ER 2006 - the 25th International Conference on Conceptual Modeling.

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