FORM DRIVEN CONCEPTUAL DATA MODELING (DATABASE DESIGN, EXPERT SYSTEMS, CONCEPTUAL).

Persistent Link:
http://hdl.handle.net/10150/188043
Title:
FORM DRIVEN CONCEPTUAL DATA MODELING (DATABASE DESIGN, EXPERT SYSTEMS, CONCEPTUAL).
Author:
CHOOBINEH, JOOBIN.
Issue Date:
1985
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Conceptual data schema is constructed from the analysis of the business forms which are used in an enterprise. In order to peform the analysis a data model, a forms model, and heuristics to map from the forms model to the data model are developed. The data model we use is an extended version of the Entity-Relationship Model. Extensions include the addition of the min-max cardinalities and generalization hierarchy. By extending the min-max cardinalities to attributes we capture a number of significant characteristics of the entities in a concise manner. We introduce a hierarchical model of forms. The model specifies various properties of each form field within the form such as their origin, hierarchical structure, and cardinalities. The inter-connection of the forms is expressed by specifying which form fields flow from one form to another. The Expert Database Design System creates a conceptual schema by incrementally integrating related collections of forms. The rules of the expert system are divided into six groups: (1) Form Selection, (2) Entity Identification, (3) Attribute Attachment, (4) Relationship Identification, (5) Cardinality Identification, and (6) Integrity Constraints. The rules of the first group use knowledge about the form flow to determine the order in which forms are analyzed. The rules in other groups are used in conjunction with a designer dialogue to identify entities, relationships, and attributes of a schema that represents the collection of forms.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Database management.; System design.; System analysis.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Management Information Systems; Graduate College
Degree Grantor:
University of Arizona

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleFORM DRIVEN CONCEPTUAL DATA MODELING (DATABASE DESIGN, EXPERT SYSTEMS, CONCEPTUAL).en_US
dc.creatorCHOOBINEH, JOOBIN.en_US
dc.contributor.authorCHOOBINEH, JOOBIN.en_US
dc.date.issued1985en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractConceptual data schema is constructed from the analysis of the business forms which are used in an enterprise. In order to peform the analysis a data model, a forms model, and heuristics to map from the forms model to the data model are developed. The data model we use is an extended version of the Entity-Relationship Model. Extensions include the addition of the min-max cardinalities and generalization hierarchy. By extending the min-max cardinalities to attributes we capture a number of significant characteristics of the entities in a concise manner. We introduce a hierarchical model of forms. The model specifies various properties of each form field within the form such as their origin, hierarchical structure, and cardinalities. The inter-connection of the forms is expressed by specifying which form fields flow from one form to another. The Expert Database Design System creates a conceptual schema by incrementally integrating related collections of forms. The rules of the expert system are divided into six groups: (1) Form Selection, (2) Entity Identification, (3) Attribute Attachment, (4) Relationship Identification, (5) Cardinality Identification, and (6) Integrity Constraints. The rules of the first group use knowledge about the form flow to determine the order in which forms are analyzed. The rules in other groups are used in conjunction with a designer dialogue to identify entities, relationships, and attributes of a schema that represents the collection of forms.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectDatabase management.en_US
dc.subjectSystem design.en_US
dc.subjectSystem analysis.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineManagement Information Systemsen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.committeememberNunamaker, Jay F.en_US
dc.contributor.committeememberKonsynski, Benn R.en_US
dc.contributor.committeememberGreenfield, Arnieen_US
dc.identifier.proquest8526308en_US
dc.identifier.oclc696633323en_US
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