Persistent Link:
http://hdl.handle.net/10150/184923
Title:
Data manipulation in collaborative research systems.
Author:
Lynch, Kevin John.
Issue Date:
1989
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:
This dissertation addresses data manipulation in collaborative research systems, including what data should be stored, the operations to be performed on that data, and a programming interface to effect this manipulation. Collaborative research systems are discussed, and requirements for next-generation systems are specified, incorporating a range of emerging technologies including multimedia storage and presentation, expert systems, and object-oriented database management systems. A detailed description of a generic query processor constructed specifically for one collaborative research system is given, and its applicability to next-generation systems and emerging technologies is examined. Chapter 1 discusses the Arizona Analyst Information System (AAIS), a successful collaborative research system being used at the University of Arizona and elsewhere. Chapter 2 describes the generic query processing approach used in the AAIS, as an efficient, nonprocedural, high-level programmer interface to databases. Chapter 3 specifies requirements for next-generation collaborative research systems that encompass the entire research cycle for groups of individuals working on related topics over time. These requirements are being used to build a next-generation collaborative research system at the University of Arizona called CARAT, for Computer Assisted Research and Analysis Tool. Chapter 4 addresses the underlying data management systems in terms of the requirements specified in Chapter 3. Chapter 5 revisits the generic query processing approach used in the AAIS, in light of the requirements of Chapter 3, and the range of data management solutions described in Chapter 4. Chapter 5 demonstrates the generic query processing approach as a viable one, for both the requirements of Chapter 3 and the DBMSs of Chapter 4. The significance of this research takes several forms. First, Chapters 1 and 3 provide detailed views of a current collaborative research system, and of a set of requirements for next-generation systems based on years of experience both using and building the AAIS. Second, the generic query processor described in Chapters 2 and 5 is shown to be an effective, portable programming language to database interface, ranging across the set of requirements for collaborative research systems as well as a number of underlying data management solutions.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Management information systems; Information resources management; Research -- Data processing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Business Administration; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Goodman, Seymour E.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleData manipulation in collaborative research systems.en_US
dc.creatorLynch, Kevin John.en_US
dc.contributor.authorLynch, Kevin John.en_US
dc.date.issued1989en_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.abstractThis dissertation addresses data manipulation in collaborative research systems, including what data should be stored, the operations to be performed on that data, and a programming interface to effect this manipulation. Collaborative research systems are discussed, and requirements for next-generation systems are specified, incorporating a range of emerging technologies including multimedia storage and presentation, expert systems, and object-oriented database management systems. A detailed description of a generic query processor constructed specifically for one collaborative research system is given, and its applicability to next-generation systems and emerging technologies is examined. Chapter 1 discusses the Arizona Analyst Information System (AAIS), a successful collaborative research system being used at the University of Arizona and elsewhere. Chapter 2 describes the generic query processing approach used in the AAIS, as an efficient, nonprocedural, high-level programmer interface to databases. Chapter 3 specifies requirements for next-generation collaborative research systems that encompass the entire research cycle for groups of individuals working on related topics over time. These requirements are being used to build a next-generation collaborative research system at the University of Arizona called CARAT, for Computer Assisted Research and Analysis Tool. Chapter 4 addresses the underlying data management systems in terms of the requirements specified in Chapter 3. Chapter 5 revisits the generic query processing approach used in the AAIS, in light of the requirements of Chapter 3, and the range of data management solutions described in Chapter 4. Chapter 5 demonstrates the generic query processing approach as a viable one, for both the requirements of Chapter 3 and the DBMSs of Chapter 4. The significance of this research takes several forms. First, Chapters 1 and 3 provide detailed views of a current collaborative research system, and of a set of requirements for next-generation systems based on years of experience both using and building the AAIS. Second, the generic query processor described in Chapters 2 and 5 is shown to be an effective, portable programming language to database interface, ranging across the set of requirements for collaborative research systems as well as a number of underlying data management solutions.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectManagement information systemsen_US
dc.subjectInformation resources managementen_US
dc.subjectResearch -- Data processing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineBusiness Administrationen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorGoodman, Seymour E.en_US
dc.contributor.committeememberRam, Sudhaen_US
dc.contributor.committeememberVogel, Douglasen_US
dc.identifier.proquest9013180en_US
dc.identifier.oclc703443154en_US
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