KNOWLEDGE SHARING AND NEGOTIATION SUPPORT IN MULTIPERSON DECISION SUPPORT SYSTEMS

A number of DSS for supporting decisions by more than one person have been proposed. These can be categorized by spatial distance (local vs. remote), temporal distance (meeting vs. mailing), commonality of goals (cooperation vs. bargaining), and control (democratic vs. hierarchical). Existing frameworks for model management in single-user DSS seem insufficient for such systems. This paper views multiperson DSS as a loosely coupled system of model and data bases which may be human (the DSS builders and users) or computerized. The systems components have different knowledge bases and may have different interests. Their interaction is characterized by knowledge sharing for uncertainty reduction and cooperative problem-solving, and negotiation for view integration, consensus-seeking, and compromise. Requirements for the different types of multiperson DSS can be formalized as application-level communications protocols. Based on a literature review and recent experience with a number of multiperson DSS prototypes, artificial intelligence-based message-passing protocols are compared with database-centered approaches and model-based techniques, such as multicriteria decision making.Information Systems Working Papers Serie

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference

Toward overcoming accidental complexity in organisational decision-making

This paper takes a practitioner's perspective on the problem of organisational decision-making. Industry practice follows a refinement based iterative method for organizational decision-making. However, existing enterprise modelling tools are not complete with respect to the needs of organizational decision-making. As a result, today, a decision maker is forced to use a chain of non-interoperable tools supporting paradigmatically diverse modelling languages with the onus of their co-ordinated use lying entirely on the decision maker. This paper argues the case for a model-based approach to overcome this accidental complexity. A bridge meta-model, specifying relationships across models created by individual tools, ensures integration and a method, describing what should be done when and how, and ensures better tool integration. Validation of the proposed solution using a case study is presented with current limitations and possible means of overcoming them outlined

Knowledge and Metadata Integration for Warehousing Complex Data

With the ever-growing availability of so-called complex data, especially on the Web, decision-support systems such as data warehouses must store and process data that are not only numerical or symbolic. Warehousing and analyzing such data requires the joint exploitation of metadata and domain-related knowledge, which must thereby be integrated. In this paper, we survey the types of knowledge and metadata that are needed for managing complex data, discuss the issue of knowledge and metadata integration, and propose a CWM-compliant integration solution that we incorporate into an XML complex data warehousing framework we previously designed.Comment: 6th International Conference on Information Systems Technology and its Applications (ISTA 07), Kharkiv : Ukraine (2007

Towards a prioritization of needs to support decision making in organizational change processes

A focus on needs and the ability to generate knowledge about needs is highly valuable for organizations because it extends the range of possible solutions and therefore enables them to create more innovative and sustainable products and services. Our paper will explore how a framework based on an abductive reasoning process for the creation and discovery of knowledge about needs in organizations can look like and what the main steps of such a framework are, in order to integrate this approach into the model of the knowledge-based firm. Moreover we will present empirical findings from a project with Austrian companies where this framework has been used

ON INTEGRATING HYPERMEDIA INTO DECISION SUPPORT AND OTHER INFORMATION SYSTEMS

The goal of this research is to provide hypermedia functionality to all information systems that interact with people. Hypermedia is a concept involving access to information, embodying the notions of context-sensitive navigation, annotation and tailored presentation. We present the architecture of a system-level hypermedia engine, designed both to manage full hypermedia functionality for an information system and to bind interface-oriented front-end systems with separate computation-oriented back-end systems. The engine dynamically superimposes a hypermedia representation over a back-end application's knowledge components and processes. The hypermedia engine generates this representation using bridge laws, which capture the internal structure of client systems. Users access the application through its hypermedia representation. We also describe a set of minimal requirements for integrating our hypermedia engine with an information system. We believe these guidelines apply to all integration efforts, not just our own. Information systems will require some supplementary routines for the engine to manage hypermedia functionality for them. The more sophisticated and cooperative the information system, the higher the level of hypermedia support the engine will provide.Information Systems Working Papers Serie

HYPER MODEL MANAGEMENT SYSTEMS

In this paper we study the integration of Model Management and Hypertext systems to produce a Hyper Model Management System (HMMS). Model Management Systems constitute a class of software that is designed to support the construction, storage, retrieval, and use of models in the context of decision support systems (DSS). Hypertext systems allow users to split information into data fragments which the user cart browse to find information by taking non-linear paths in computer based texts. It has been suggested that DSSs should be conceived as environments which support decision making. We support the view that such environments can be readily provided for the subtask of model management by hypertext systems. The different kinds of model knowledge can be captured within different types of hypertext nodes and the relationships among these can be maintained by hypertext links. In this paper we describe some aspects of model management where hypertext will have a significant impact. However, plain hypertext is ineffective in dealing with the dynamic nature of information in model management tasks where data is revised, models executed, and reports are created on the fly. Dynamic domains require dynamic hypertexts. In this paper we also study the requirements for dynamic hypertexts. These can be satisfied within the class of generalized hypertext systems by using special hypertext nodes and links which we describe. We explore different architectures to integrate MMS and Hypertext systems to obtain HMMSs. This paper emphasizes the need for a shift to integrating Model Management and hypertext technologies.Information Systems Working Papers Serie