Knowledge that Transforms

:An architectural approach is used to provide a framework for understanding the Enterprise-wide Information Management Complex (ewimc). Imc is proposed as an emerging self-contained business process that interfaces with but remains separate from all other business elements, while providing unique services to those other elements. A generic model of ewimc itself is presented that breaks down imc into a set of systems federations, each functionally distinct from one another; each federation, in turn, is composed of more specific systems and each system its subsystems, and so on. Thus, a top-down, hierarchical approach is applied to the concept of imc to provide a framework for understanding the complexities and interrelationships among its many pieces. The model is offered as a first step in developing a comprehensive overview of ewimc to replace the numerous fragmented approaches offered in the past. An example of General Motors’ architecture is presented. Finally, the System Planning Technique is presented as a tool for defining systems requirements.

:The usefulness of strategic decision support systems (sdsss) has been a highly discussed, yet under-investigated issue. This paper attempts to help fill the gap between available subjective/argumentative theory and the necessary empirical evidence to evaluate and implement existing claims and design methodologies.An empirical study is described that explicitly focused on the usefulness of information in a strategic decision-making context. Factor analysis was employed in the derivation of five orthogonal dimensions of the usefulness of strategic information. The results suggest that strategic systems planning [20] may be preferable to historical, traditional approaches to providing useful information to strategic decision makers in a sdss context. A research agenda is discussed that suggests avenues for studying strategic systems planning in the context of various planning processes contributing to sdss development, of knowledge-based sdsss, and of strategic expert systems.

:In the distributed processing environment characteristic of the management information systems of today, a need to superimpose an additional information flow onto an existing computer communication network arises frequently. The situation may result from a company’s expanding needs for communication over its private or a shared network, or because a new user company is joining an existing shared network. In order to accommodate the new information flow without negatively affecting the waiting times for the previously contracted communications, network capacity may have to be expanded. We present an algorithmic method for least-cost capacity expansion of a set of network paths preselected to carry the incremental information flows. Owing to the insights gained as a result of extensive computational experiments, we then provide a simplified technique applicable to a broad class of cases. Polynomial time complexity of the algorithms included in the presented methodology points to its practicality.

:Arguments are presented in support of the evolutionary development of information systems. The traditional analysis and design tools are shown to be inappropriate for the evolutionary development, and the requirements for such a development environment are determined. Three major tools are borrowed from the fields of artificial intelligence, programming languages, and database management, and combined to create an environment that meets these requirements. The resulting novel system architecture is described by using a university registration system.

:While information is recognized as an important corporate resource, its management has not been accomplished to the extent of other major resources. A major reason for this condition is that the information resource is not as well defined as other resources. To manage any resource effectively, the nature of that resource must be well defined. In this article, we first propose a model for corporate data. This model represents the data definition or “metadata” for Information Resource Management (irm). Through this metadata we define the “state” of the information resource. We characterize a set of dimensions for metadata and discuss its representation and management. Concepts from Information Resource Dictionary Systems (irds) are described as they support metadata management. We include irds contents, capabilities, and implementation issues. Finally, we assess the diverse impacts of metadata management on related Information System (is) issues such as end-user computing, corporate is planning, information architecture development, and information system development.

:The paper attempts to model internal controls in an organization from a database perspective. It provides a three-level architecture to integrate data, process, and control level Abstractions. A semantic formalism based on this architecture is presented.

:This paper reports on results from a longitudinal case study on use of a spreadsheet program (sp).The work reported here focuses on:—spreadsheet program users’ perceptions of the sp and their information environment (including sp models).—changes in users’ perceptions of their information environment and the sp.The approach has its roots in Kelly’s personal construct theory [31] and in cognitive complexity theories [43, 54, 55]. A version of Kelly’s Role Construct Repertory Interview (rcri) was used to collect data at different points of time over a period of thirteen months. The data were transformed into a measure of integrative complexity and analyzed.The study provides insight into the impact of end-user-developed computer-based models (decision support systems).

:This paper addresses the treatment of uncertainty in expert system shells. A review of the modeling of uncertainty by expert system shells is presented. An experiment to replicate earlier work investigating the manner in which individuals manipulate certainty factors in comparison to commercial shells is discussed. Comparisons are made between seven commercial shells, both personal computer (pc) and mainframe based, and individuals. A significant difference between individuals and shells as well as among shells themselves is indicated. Some implications for both expert system and decision support sytem (dss) methodologies are discussed.

Information centers (ics) are taking on an increasingly important role in organizational computing and are being given responsibility for supporting the enhancement of information system technology in the organization. There are primarily three areas of responsibility for the ics: consultation, distribution, and help service. The information center expert (ice) project attempts to provide knowledge-based support for ics. The ice project has three divisions, corresponding with the three areas of responsibility for information centers. The three divisions are: information center expert for consultation (ice/c), distribution (ice/d), and help service (ice/h). The ice/c system has been developed using Expert System Environment/Virtual Machine (ese/vm) on the IBM 4381 mainframe. The system is operational and is being tested in five different ics. ice/c is used for consultation with ic users to assist them with the process of software selection. The paper presents the ice/c architecture and discusses functional extensions to ice/c, that is, ice/d and ice/h, for supporting the other responsibilities of the <SCIC . The design considerations for these extensions are discussed. The development of ice/c surfaced concerns regarding acquiring knowledge from multiple experts. An alternative approach using a group decision support environment to elicit knowledge from experts is presented. The paper also discusses the use of an objectoriented approach as a representation technique.Key Words and Phrases:: Knowledge-based systemsexpert systemsinformation centerknowledge acquisitionobject-oriented systems Additional informationNotes on contributorsJay F. NunamakerJay F. Nunamaker, Jr., is head of the Department of Management Information Systems and is Professor of Management Information Systems (mis) and Computer Science at the University of Arizona. He received a Ph.D. from Case Institute of Technology in systems engineering and operations research. He was an Associate Professor of Computer Science and Industrial Administration at Purdue University. Dr. Nunamaker joined the faculty of the University of Arizona in 1974 to develop the mis program. Author of more than 75 papers on group decision support systems, the automation of software construction, performance evaluation of computer systems, and decision support systems for systems analysis and design, he has lectured throughout Europe, Asia, and South America, as well as the USSR. Dr. Nunamaker is chairman of the Association for Computing Machinery (ACM) Curriculum Committee on Information Systems.Benn R. KonsynskiBenn R. Konsynski—please see the biography in the Introduction.Minder ChenMinder Chen is a Ph.D. candidate in the Department of Management Information Systems at the University of Arizona. He received a B.S. in Electrical Engineering from National Taiwan University and an M.B. A. from National Chiao-Tung University. His current research interests include computer-aided software engineering, software productivity, the object-oriented approach to information systems development, knowledge acquisition and representation in system analysis and design, expert system applications, and knowledge-based supported collaborative work.Ajay S. VinzeAjay S. Vinze is Assistant Professor of Management Information Systems at Texas A&M University. He received a B.Comm. from the University of Delhi and an M.B.A. from the University of Connecticut. He received his Ph.D. in management information systems from the University of Arizona in May 1988. The title of his dissertation is "Knowledge-based Support for Software Selection in Information Centers: Design Criteria, Development Issues, and Empirical Evaluation." His current research interests include business applications for expert system technology, end-user computing and information centers, and decision support systems.Y. Irene Liou ChenY. Irene Liou Chen is a Ph.D. candidate in the Department of Management Information Systems at the University of Arizona. She received a B.A. in philosophy from National Taiwan University, an M.L.S. from the University of Southern Mississippi, and an M.S. from the University of Arizona. Her current research interests include knowledge-based systems development, knowledge acquisition from multiple experts, the information center in an academic environment, expert systems design for end-user computing and business applications, and group decision support systems.Mari M. HeltneMari M. Heltne is Assistant Professor of Management Information Systems at Luther College in Decorah, Iowa. She received her Ph.D. in management information systems from the University of Arizona in May 1988. Her research interests include knowledge-based systems in business, particularly for resource management, and support mechanisms for end-user computing.