Conceptual Modeling of Information SystemsIt 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. |
Contents
| 1 | |
Entity Types | 37 |
Relationship Types | 59 |
Cardinality Constraints | 83 |
Particular Kinds of Relationship Type 103 5 1 Reference Relationship Types | 103 |
Reification | 123 |
Generic Relationship Types | 137 |
Derived Types | 157 |
Action Request Events 277 | 276 |
State Transition Diagrams | 299 |
Statecharts | 325 |
Use Cases 337 | 336 |
Case Study | 353 |
Metamodeling 383 | 382 |
The MOF and XMI | 415 |
References | 431 |
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Common terms and phrases
action association assume attribute binary called cardinality chapter characteristics Class classification Committee complete conceptual modeling conceptual schema condition consider consists constant constraint contains context corresponding create defined definition dependency derivation rule described disjoint domain event type effect element Employee entity type example exist expression Extension facts Figure formal Fragment functions given gives identifiable information base information system instance integrity kinds knowledge language logic machine Manager Materializes means meta metaschema name:String Natural Note object occurs operation participant particular perform permanent Person play population presented properties provides quantity query reference relationship type rental representation represented request requirements reservation respect role Sale satisfy sentences shown in Fig shows simple specialization specification stereotype String structural Student subtype tion Town transition transition diagrams users Woman