5.1.1 Information models are regarded widely as beneficial by saving cost through realignment of processes, risk reduction and elimination of redundancy. Information models convey ideas and facilitate the analysis and understanding of complex processes and structures. These models form the basis for software engineering practices that build systems and databases, redefine organizational structures, improve business processes, and develop standards.

5.1.2 This practice provides a practical means for developers and users of information models to employ appropriate modeling methods and to objectively determine model quality.

5.2.1 Models are representations of past, existing, or contemplated reality. Models may assist in the explanation or analysis of complex structures and processes that may exceed human capacity for direct visualization or understanding. Models enable a focus on the key elements of a process or structure while ignoring confounding or irrelevant elements. As such, models make an explicit statement of the meaning of the reality being modeled.

5.2.2 Integrated information engineering models provide a coherent view of the processes and data of an organization or enterprise ( 5 ) . Activity models identify the fundamental tasks performed in a function. Process models accurately describe the detailed collection of these activities within an organization. Data models are derived from and support the functions described in activity models. Object models also characterize the processes and data required to understand business operations. Both structured and object-oriented models may be used to construct information systems that support those business operations. Application models describe in varying levels of detail, the overall architecture and components of the software needed to support the envisioned business functions. Organizational models reflect the current and envisioned future state of the organization, especially as this impacts business processes enabled or supported by information systems. Location models identify and describe the business and geographic position and relationships of structural components of an organizational entity. Technology models describe in varying levels of detail those hardware, system software, and network components needed to operate the information systems supporting a business area.

Models may be textual, graphic, or mixed graphic and text forms, including, tables and structured lists, flowcharts, process flow diagrams, state diagrams, data flow diagrams, entity-relationship diagrams, and related techniques develop an understanding of business processes and the transformation of data through these processes ( 6 ) . Modeling products may also relate two or more types of models, such as for an Application-Data Matrix, or Technology-Location Plan.

5.3.1 Since proposed by Zachman in 1987 ( 3 ) , the Information System Architecture (ISA) has become one of several means to view and to blueprint information systems within an entire organization, to design business processes and change enterprise strategies, and to describe and interrelate the components of an information system to the entire organization. The cells within the framework represent primitive architectural constructs where the sets of columns collectively represent a consistent integrated model for each perspective (row). These rows describe different types of artifacts, each having a different purpose:

5.4.1 Modeling activities have been prevalent throughout the history of the engineering disciplines. This rich history indicates four basic principles ( 7 ) :

5.4.2 The three approaches to information modeling are characterized as top-down, bottom-up, and inside-out ( 8 ) . Of these, the top-down and bottom-up approaches are most often used.

5.6.1 System engineering is considered in all leading system lifecycle methodologies as a sequential, cyclic, or iterative sequence of four essential activities from a visionary or inception activity to deployment or implementation ( 9 ) as illustrated in Fig. 1 . Performance and outcome of these activities can be substantially improved through modeling. For example, system development models may consist of elementary structures like an organizational chart to detailed structural representation of a software package. Models typically are employed in the planning and analysis phase of software development, in system and software design, and in the coding process.

5.6.2 Modeling in Systems Inception Analytical models are essential to the systems inception and planning. In the inception phase, models help develop the business rationale and communicate this rationale in the system business case. Semantic and diagrammatic models help explain the thought processes leading to a system proposal. Activity models are useful to design future business activities and business process improvement. Financial models and simulations are important components of the business case and risk prediction ( 11 ) , and for software engineering project management ( 12 , 13 ) , and estimation ( 14 ) .

5.6.3 Modeling in Systems Elaboration The elaboration phase of the systems development paradigm includes analysis and high level design. Models are essential to system elaboration by analyzing, recording, and detailing business process and system functionality. Typical examples of analytical and high level design models include business process flow diagrams, conceptual entity models, conceptual technology models, etc.

5.6.4 Migration of Models in System Construction A software engineering methodology provides development paradigms as a procedural framework for the design, construction, testing and implementation of systems. Within a development methodology, modeling methods prescribe the symbology and heuristics used to create models of varying levels of detail. Automation, via computer-assisted software engineering (CASE) tools, facilitates the modeling process and provides the vehicle that achieves transformability. The transformation from analysis to a functioning system is termed forward engineering while transformation from a functioning system to analytical or design models is termed reverse engineering.

The benefit of using standardized modeling methods is the software models that are created are easily understandable and readily transformable to a functioning system ( 10 ) . As illustrated in Fig. 2 , models follow a logical progression from Conceptual to Logical to Physical ( 8 , 15 ) . Fig. 2 also illustrates the relationship between system lifecycle phases and Zachman Framework, along with representative types of business process and data models. This cascade of models facilitates the understanding of concepts and the implementation of information applications, databases or systems.

The systems development process originates with either an existing system in need of improvement or a vision of a new or reengineered system. The chain of models begins with conceptual modeling where activities and data are modeled at a high level of detail.

5.6.5 Organizational Issues The structure and process elements of the model quality paradigm involve the creation and maintenance of an environment and procedures that facilitates creation, evaluation, communication, and utilization of information models. For the system development organization there should be a component responsible for the creation and maintenance of models. The organization should establish policies for modeling and standardize the model development process, methodologies, and tool sets. These policies constitute internal, or organizational standards or conventions, consisting of the following:

5.7.1 Organizations may develop their own internal standards, such as standard operating procedures, or they may develop standards for use by the public, an industry or professional community, or other group of consumers. Modeling facilitates the development, communication and understanding of both internal and industry-wide standards. Developers of internal and external standards may use models to prepare and present a common reference to their work. Furthermore, consumers may find models facilitate the implementation and use of standards by their organizations by providing standards users a blueprint from which they can tailor and optimize model components for implementation. Here adherence to the structure, process, and outcome quality requirements shall be especially rigorous since the models produced provide the foundation for standards that may have substantial industry impact.