Synopses & Reviews
Data modeling was hypothesized to be the "salvation" of an organization's data problems. This book aims to analyze the problems encountered and to present a comparative philosophical study of the various approaches. On the philosophical level, the authors explore the epistemology, ontology, and rationality of each modeling approach. While on the theoretical computer science level, a systematic study of the history and development of three major strands of data modeling is presented. This book will be of great interest to all computer scientists using information systems as well as philosophers with an interest in computing applications.
Review
"I strongly recommend this book to people who view information systems only as a technology and do not remember that any technology that can change the way people live and work is necessarily a social and philosophical subject." G. Rumolo, Computing Reviews
Review
"This is an intellectually challenging, demanding, and mind-stretching book, valuable both as a summary of currant knowledge about the subjects of information systems development and data modeling and for the insights it gives about alternative approaches." Adele M. Fasick, The Library Quarterly
Synopsis
Summarises ideas in Information Systems Development for graduate students and professionals.
Synopsis
Data modelling was hypothesised to be the salvation of an organisation's data problems. This book aims to analyse the problems encountered and to present a comparative philosophical study of the various approaches. The authors explore the epistemology, ontology and rationality of each modelling approach, and describe the underlying assumptions embedded in them.
Table of Contents
1. Introduction; 2. Definition and evolution of information systems development methodologies and data modeling; 3. Philosophical foundations; 4. Conceptual and paradigmatic foundations of ISD; 5. Paradigmatic analysis of ISD methodologies; 6. Conceptual and paradigmatic foundations of data modeling; 7. Paradigmatic analysis of data modeling approaches; 8. Conclusions; Appendix A. Summaries of selected methodologies; Bibliography; Index.