Developing foundations for knowledge management systems

Knowledge Management (KM) is an important issue in organizations. However there are several barriers to successful KM. In particular, knowledge hoarding, difficulties in identifying organizational knowledge, not understanding KM requirements, and technical difficulties of knowledge representation. In this work we focus on a connection between the managerial and technical aspects of knowledge management. We study the nature of organizational knowledge in order to derive knowledge management requirements to support the design of computerized Knowledge Management Systems. The work consists of three parts: 1) Defining organizational knowledge that needs to be managed. 2) Using the definition of organizational knowledge and its attributes to identify knowledge management requirements. This involves identifying the various facets of knowledge as well as the perceived meta- knowledge requirements of users. 3) Deriving guidelines for the efficient design of knowledge management systems

A FRAMEWORK TO CLARIFY THE ROLE OF KNOWLEDGE MANAGEMENT SYSTEMS

Knowledge management Systems (KMS) are IT applications that manage representations of organizational knowledge. This paper presents a conceptual model of KMS which adapts an artificial intelligence (AI) based view of knowledge. According to this view, knowledge can be defined in terms of agent, action, state, and goal. The conceptual model is intended to help differentiate the role of KMS from that of Information Systems (IS). The knowledge managed by the KMS is intended to enable an agent to choose actions that can be taken to accomplish a goal in the given state. The role of the IS is to make the agent aware of a situation described in terms of states, actions, and goal. The model suggests that whether we classify an IT application as KMS or IS depends on the contents it manages and to increase the effectiveness of KMS, it is often necessary to use IS that complement the KMS. Considering the importance and popularity of KMS in organizations, we believe the clarification of the role of KMS is useful

A Conceptual Model and Typology for Information Systems Controls

Controls are widely used in business and are often related to information technology (IT) because IT systems are used to implement business controls and because the introduction of IT entails additional control concerns. Thus, control aspects should be part of information systems analysis and design. Furthermore, information systems need to be examined for completeness and correctness of their controls. However, despite the importance of IT controls, no general, well formalized framework is available to guide the analysis of controls requirements, the design of controls in systems, and the audit of existing systems. This paper presents a conceptual framework of controls based on an ontological foundation and an extended typology of IT controls. The framework can be used to analyze IT control issues and manage IT control assets. An initial evaluation of the typology using a published control framework and an example indicates its potential usefulness

AN ONTOLOGICAL ANALYSIS OF SOME FUNDAMENTAL INFORMATION SYSTEMS CONCEPTS

This paper describes how ontological concepts can be used to model information systems. We view an information system as an object that is independent of its use or its technology of implementation. The main premise of the model is that an information system is a representation of a real-world system, and as such it should possess certain characteristics, We show how the model can be used to define various concepts such as real-time, batch, data processing, management reporting, decision support, controls, and decomposition. Furthermore, we show how the model may serve as the foundation of a theory of systems analysis and design. In particular, it provides a formal definition of information systems specifications and a normative model of decomposition

A UNIFIED MODEL OF SOMWARE AND DATA DECOMPOSITION

Decomposition is an important part of information systems analysis and design and is manifested as the breakdown of the system to elements such as subsystems, modules, activities, processes, entities, and objects. Good decomposition is considered a major requirement for a good system design. However, there is no comprehensive theory of information systems decomposition and no single dominant decomposition approach exists. Consequently, software decomposition relies on guidelines and designer\u27s experience. In this article, we propose a foundation for a theory of good decomposition based on two principles: 1) the decomposition of an information system should reflect the nature of the real world system represented by it, and 2) static and dynamic aspects of systems cannot be separated and hence good decomposition should be based on both. The model enables the analysis of concepts such as good software modules, normalized relations, objects, and entities as special cases of one generalized construct

A FOUNDATION FOR OPEN INFORMATION ENVIRONMENTS

Traditionally, information systems were developed within organizations for use by known audiences for known purposes. Advances in information technology have changed this landscape dramatically. The reach of information systems frequntly extends beyond organizational boundaries for use by unknown audiences and for purposes not originally anticipated. Individuals and informal communities can generate and use information in ways previously restricted to formal organizations. We term applications with these characteristics open information environments (OIEs). OIEs are marked by diversity of information available, flexibility in accommodating new sources, users and uses, and information management with minimal controls on structure, content, and access. This creates opportunities to generate new information and use it in unexpected ways. However, OIEs also come with challenges in managing the semantic diversity, flexibility of use, and information quality issus arising from the range of users and lack of controls. In this paper, we propose a set of principles for managing OIEs effectively. We outline a research program to examine the potential of OIEs, the challenges they present, and how to design OIEs to realize the benefits while mitigating the challenges. We highlight our ongoing research in this area, and conclude with a call for more research on this important phenomenon

TOWARD A THEORY OF THE DEEP STRUCTURE OF INFORMATION SYSTEMS

The deep structure of an information system comprises those properties that manifest the meaning of the real-world system that the information system is intended to model. In this paper we describe three models that we have developed of information systems decl}.structure properties. The first, the representational model, proposes a set of constructs that enable the ontological completeness of an information systems grammar to be evaluated. The second, the state-tracking model, proposes four requirements that information systems must satisfy if they are to faithfully track the real-world system they are intended to model. The third, the good-decomposition model, proposes a set of necessary conditions that an information system must meet if it is to be well decomposed. The three models facilitate the evaluation of grammars used to analyze, design, and implement information systems and specific scripts that represent implemented information systems

Goal-Driven Multi-Process Analysis.

Extant process modeling techniques address different aspects of processes, such as activity sequencing, resource allocation, and organizational responsibilities. These techniques are usually based on graphic notation and are driven by practice rather than by theoretical foundations. The lack of theoretical principles hinders the ability to ascertain the correctness of a process model. A few techniques (notably Petri Nets) are formalized and apply verification mechanisms (mostly for activity sequencing and concurrency). However, these techniques do not deal with important aspects of process design such as process goals. As previously suggested, a formal process modeling framework, termed the Generic Process Model (GPM), has been used to define the notion of process model validity. In GPM, validity is based on the idea that the purpose of process design is to assure that an enacted process can reach its goal. In practice, often several processes work together to accomplish goals in an organizational domain. Accordingly, in this paper we extend the validity analysis of a single process to a cluster of processes related by the exchange of physical entities or information. We develop validity criteria and demonstrate their application to models taken from the Supply Chain Operations Reference-model (SCOR). We also use the formal concepts to analyze the role of an information system in inter-process communication and its possible effects on process cluster validity

A MODEL OF SYSTEMS DECOMPOSITION

The way in which systems should be decomposed so they can be better understood and better designed remains a fundamental problem in the information systems discipline. A number of different decomposition methodologies have been proposed. However, no methodology has emerged as dominant, presumably because the relative strengths and limitations of each methodology are still unclear. Case study research that has compared the methodologies, for example, has produced only equivocal results. In the absence of a theory of decomposition, it is difficult to make insightful predictions about the merits and failings of a particular methodology. Consequently, it is difficult to undertake empirical research that produces compelling results. Accordingly, in this paper we develop a rudimentary model of decomposition that we hope might form the basis of a subsequent, more complete theory of decomposition