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Chap 7
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Background and References
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When the view models have been transformed as indicated to accommodate the database model, the views presented by the original applications have been broadened and perhaps altered It is desirable to maintain a description of the database in terms of the original view models, since that provides the documentation for the design In order to accommodate access to the database after integration, we de ne further database submodels Database submodels permit an application to access the integrated database, taking advantage of new relations to which access has been made available, and at the same time presenting the structure and attributes largely in terms of its original model Sometimes it is better to adapt the database submodel to be a proper subset of the integrated database, since this may provide a more realistic view of the actual operation and its constraints When database submodels are subsets in the database model, such a transformation from database model to database submodel only requires selection and can be easily achieved When substantial transformations have taken place, automatic transformation of queries phrased according to di erent submodels is di cult to achieve We see little of that concept in practice An approach to this problem is presented in Sec 9-6, in an example of a database-system implementation Means to describe the relationships in the database are shown in the next chapter
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BACKGROUND AND REFERENCES
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In order to develop the conceptual basis for database planning we have used relations as the basic units and classi ed ve types of relations in order to describe the required choices Many other models to aid database design have been developed and have in uenced the concepts presented here The relational model which provides the basis for the conceptual view presented in this chapter allows a great deal of formal analysis Several early papers (Langefors63 , Levien67 , and Childs68 ) suggested the use of a model based on set theory to describe le and database structures Most of the current activity was kicked o by EF Codd, who, in a series of papers (Codd70,74 , and in Rustin72) , presented the relational model in terms of its relevance to database design and implementation In a second paper in Rustin72 , Codd describes the required operations and their power Associated early contributions are Heath and Date in Codd71 , Delobel73 , Armstrong74 , Wang75 , and Forsyth in King75 , which provided mathematically oriented criteria for the optimization, manipulation, and demonstration of the correctness of the manipulations in relational models Fagin77 de ned multivalued dependencies and a fourth normal form Up to seven normalizations have been proposed (Beeri78 ) Issues of relational decomposition are summarized by Maier80 The mathematical theory of dependencies in databases is now a sub eld of its own, with a rapidly exploding literature The set of axioms de ning transformations is due to Armstrong74 A basic text is Ullman82 and recent results may be found in journals, see for instance, Sadri82 and in the proceedings of the ACM-PODS conferences (Aho82 )
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A tool in the developmemt of dependency theory is the universal relation All data is placed into a single abstract unnormalized relation representing all entities and all their attributes Many cells will be null The formal knowledge to manipulate the universal relation consists of a collection of various dependencies which relate the attributes In our structural model we avoid many of these issues by concentrating on the simpler view models The practical importance and su ciency of Boyce-Codd-normal form was presented by LeDoux82 Date in Tou74 expresses strongly the distinction between the database submodel and the database model Several related papers appear in King75 Integration of databases is presented by ElMasri79 , Hubbard81 , and Navathe82 It also appears as phase in Schkolnick78 and Lum79 Generalization of entities is addressed by Smith77 The concept of multiple linked databases is due to Litwin81L and tested within the POLYPHEME projectLanguages to describe the semantics have been de ned by Mylopoulos80 and Hammer81 Work by Earley71,73 is oriented toward language aspects of relational structures In order to construct relevant database models, the semantics of the interrrelational structure have played an important part in this chapter Work by Schmid in King75 and Manacher in Kerr75 was especially in uential ElMasri80 compares the how the structural concepts are modeled in alternative schemes Questions of semantic relevance of the structure of databases were analyzed in Langefors73 , Dehene e74 , Hainaut74 , Robinson in Douque76 , and Roussopoulos in Kerr75 Kent78 reports on experience with a conceptual modeling tool Integration of relations can lead to null entries Vassiliou80 , Goldstein81 , Lipski79 , and Zaniolo82 consider the problem of nulls, Imielinski81 extends the relational operations to deal with nulls Later work by Codd79 and Date82 extends the semantics of the original relational model The new model, RM/T, includes 5 referenced relation types and 8 integrity rules, which can be mappped into the structural model An exhaustive review is in Date82 Some of this work is in uenced by the concepts of semantic nets; a comprehensive reference is Schank73 Joins are extended by LaCroix76 Other types of models can be easily related to the concepts presented here Some of the models which are attracting attention are summarized here Entity models use the concept of the entity as their basic unit Data structures are composed of entities de ned by information requirements Entities have properties, which were in our model decomposed into attributes, subsets, or data elements Extending entities with the notion of relationships, as done by Chen76 , extends the descriptive capability, and this work has also spawned much interest, collections are found in Chen80 and successor proceedings Relationships may be simple (1 : n), as our ownership and reference connections, or m : n, as modelled by associations and other multiple connections Such relationships are essential, since the information is stored within them The guidance given by these models tends to be less formal than the rules based on relations Functional models formalize the relationships among entities Shipman81 provides a language to express them and Buneman82 provides a query language based on the functional concept An access-path model de nes the database as collections of sequential transformation sequences, required to obtain a physically coded entity in response to a logical query A rigorous hierarchy of the transformations allows the prediction of information loss and access cost at the various levels Entity and access-path models (DIAM) have been developed by Senko73 and compared with alternate approaches in Bachman75 and by Hall in Neuhold76 A level to model hardware functions is also available DIAM is shown to be capable of modeling many current concepts (Senko in Rustin72 , in Benci75 , in Kerr75 ,
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