Information Modeling Methods And Methodologies

The purpose of this book is to disseminate the research results and best practice from researchers and practitioners interested in and working on modeling methods and methodologies. Though the need for such studies is well recognized, there is a paucity of such research in the literature. What specifically distinguishes this book is that it looks at various research domains and areas such as enterprise, process, goal, object-orientation, data, requirements, ontology, and component modeling, to provide an overview of existing approaches and best practices in these conceptually closely-related fields. *Note: This book is part of a series entitled "Advanced Topics in Database Research.

Information modeling techniques are used during information systems analysis and design, and are important kinds of techniques, that are part of information systems development methodologies. An optimal information modeling technique may be defined as an information modeling technique that is most appropriate to be applied in a specific situation indicated by certain contingency factors. Optimal Information Modeling Techniques examines these methods and provides the most recent research in the field, to be applied to the management applications of modern organizations.

Covers central topics in information systems modeling and architectures. Includes the latest developments in information systems modeling, methods, and best practices.

This book is about the information modeling of organizations in the widest sense possible. This term express the general meaning of the term "organizational modeling" with the light flavor of informatics practices rather than just the IS or IT view of the organization. Although the topic of the cognition of organizational structure and behavior traditionally belongs to the management theory; informatics brings to this area the necessary exactness in the shape of formal specifications and a systemic style of thinking. Informatics is a source of sophisticated techniques and tools, aimed on discovering the general regularities of the organizational structure and behavior (often called "business rules") with the ability to abstract all non-contentual aspects of the organizational system. Information technology, on the other hand, is a key enabler of organizational changes as it is established in all literature mentioning the theory of business reengineering. Consequently, the well designed Information System must be a clear picture of all substantial aspects of the organization (both the structural and the behavioral ones). Information modeling aims to create the view of the organization which is, on the one hand independent of any non-contentual aspect (including the information technology at first); on the other it is fully consistent with following the process of the development of the Information System (i.e., the infrastructure in general). The book introduces the methodology for modeling the business system based on two complementary views which covers both ontology and business process model of the organization using standard languages UML and BPMN and including tools for ensuring the consistency of both models. The book also outlines the original methodology for service-oriented building of the process managed organization and discusses the problem of the process-oriented management in the field of public administration.

Information systems development is not merely a technical intervention but involves social and ethical dilemmas that affect the human, social and organizational domains. To demonstrate this point, the authors conduct a thorough and substantive description and analysis of the conceptual and philosophical underpinnings of systems development. In particular they analyse a number of systems development methodologies including structured methods, prototyping, ETHICS and Soft Systems Methodology to reveal the underlying conceptual and philosophical foundations. The book provides an in-depth analysis of data modelling theory and its links with theories of language and cognition. It offers a framework to describe and analyse different systems development approaches and to explain their strengths and weaknesses. The book is aimed at graduate students taking courses in information systems and data modelling, but will also appeal to information systems managers and professionals for whom the summary of methodologies will be useful.

This book reviews the state-of-the-art and state-of-the-practice of modeling methods and methodologies in information systems development. The book has sections on foundations of information modeling, extended object-oriented modeling and Web information systems modeling. Information Modeling in the New Millennium addresses the gap between technical and business-oriented modeling approaches by providing an integrative view of modeling different of facets of ICT and organizations.

Multilevel modelling is a data analysis method that is frequently used to investigate hierarchal data structures in educational, behavioural, health, and social sciences disciplines. Multilevel data analysis exploits data structures that cannot be adequately investigated using single-level analytic methods such as multiple regression, path analysis, and structural modelling. This text offers a comprehensive treatment of multilevel models for univariate and multivariate outcomes. It explores their similarities and differences and demonstrates why one model may be more appropriate than another, given the research objectives. New to this edition: An expanded focus on the nature of different types of multilevel data structures (e.g., cross-sectional, longitudinal, cross-classified, etc.) for addressing specific research goals; Varied modelling methods for examining longitudinal data including random-effect and fixed-effect approaches; Expanded coverage illustrating different model-building sequences and how to use results to identify possible model improvements; An expanded set of applied examples used throughout the text; Use of four different software packages (i.e., Mplus, R, SPSS, Stata), with selected examples of model-building input files included in the chapter appendices and a more complete set of files available online. This is an ideal text for graduate courses on multilevel, longitudinal, latent variable modelling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology. Recommended prerequisites are introductory univariate and multivariate statistics.

Using concise and direct language, Betsy McCoach′s book imparts a wide range of modeling techniques for use with quantitative data, including: From 2-level multilevel models to longitudinal modeling using multilevel and stuctural equation modeling (SEM) techniques. Part of The SAGE Quantitative Research Kit, this book offers the know-how and confidence needed to succeed on your quantitative research journey.

Philosophical paradigms, theoretical frameworks, and methodologies make up the answering and problem solving systems that define current research approaches. While there are multiple research method books, the subject lacks an update and integrated source of reference for graduate courses. Research Methodologies, Innovations and Philosophies in Software Systems Engineering and Information Systems aims to advance scientific knowledge on research approaches used in systems engineering, software engineering, and information systems and to update and integrate disperse and valuable knowledge on research approaches. This aims to be a collection of knowledge for PhD students, research-oriented faculty, and instructors of graduate courses.