Practical issues in knowledge management

It is easy to get caught up in the potential surrounding KM. Yes, it is promising and, if companies can realize that promise, KM will become important. In point of fact, though, KM is a difficult, time-consuming, and expensive undertaking even under the best of circumstances. Unfortunately, today's world doesn't present the best of circumstances for most enterprises. Budgetary and resource constraints combine to put IT under the microscope of definable metrics, such as return on investment. This mindset challenges KM to deliver tangible and predictable results, when most KM benefits are difficult to realistically articulate. I examine two areas that present practical problems to any KM initiative. Rather than making a statement about knowledge or how to manage it, I simply want to identify the inherent challenges that any significant KM initiative faces. Coordinating the distribution of information in large companies is a challenge. It pays to think about fitting the information you have to an appropriate communication channel     

Object-oriented database management systems: concepts and issues

Requirements imposed on both the object data model and object management by the support of complex objects are outlined. The basic concepts of an object-oriented data model are discussed. They are objects and object identifiers, aggregation, classes and instantiation mechanisms, metaclasses, and inheritance. Object-oriented models are compared with semantic, relational, and Codasyl models. Object-oriented query languages and query processing are considered. Some operational aspects of data management in object-oriented systems are examined. Schema evolution is discussed     

Building knowledge base management systems

Advanced applications in fields such as CAD, software engineering, real-time process control, corporate repositories and digital libraries require the construction, efficient access and management of large, shared knowledge bases. Such knowledge bases cannot be built using existing tools such as expert system shells, because these do not scale up, nor can they be built in terms of existing database technology, because such technology does not support the rich representational structure and inference mechanisms required for knowledge-based systems. This paper proposes a generic architecture for a knowledge base management system intended for such applications. The architecture assumes an object-oriented knowledge representation language with an assertional sublanguage used to express constraints and rules. It also provides for general-purpose deductive inference and special-purpose temporal reasoning. Results reported in the paper address several knowledge base management issues. For storage management, a new method is proposed for generating a logical schema for a given knowledge base. Query processing algorithms are offered for semantic and physical query optimization, along with an enhanced cost model for query cost estimation. On concurrency control, the paper describes a novel concurrency control policy which takes advantage of knowledge base structure and is shown to outperform two-phase locking for highly structured knowledge bases and update-intensive transactions. Finally, algorithms for compilation and efficient processing of constraints and rules during knowledge base operations are described. The paper describes original results, including novel data structures and algorithms, as well as preliminary performance evaluation data. Based on these results, we conclude that knowledge base management systems which can accommodate large knowledge bases are feasible. Edited by Gunter Schlageter and H.-J. Schek. Received May 19, 1994 / Revised May 26, 1995 / Accepted September 18, 1995     

Data management issues and trade-offs in CSCW systems

Substantial interest has developed in recent years in building computer systems that support cooperative work among groups without the need for physical proximity. This paper examines some of the difficult data management issues in designing systems for computer-supported cooperative work (CSCW). Specifically, we consider an example CSCW system to support large-scale team science over the Internet: the Collaboratory Builder's Environment. We discuss the issues of managing shared data in such systems, reducing information overload and providing group awareness and access control. We discuss several promising approaches to these issues. We point out where a significant gap remains in addressing the requirements of such systems and where designers have to make design trade-offs that can be difficult to evaluate. Finally, we discuss several open issues for future work     

Object-oriented database management systems: evolution andperformance issues

Several research prototypes and commercial object-oriented database management systems (DBMSs) that emphasize the representation and manipulation of complex objects are reviewed. It is argued that clustering and buffering schemes tailored to typical complex object operations offer the best near-term means of improving the performance of databases and that research in clustering and buffering should address recent advances in disk technology: optical and parallel disks. The object-oriented DBMSs reviewed are Orion, Iris, GemStone, Encore, Ontos, Versant, and ObjectStore     

信息系统项目管理的知识管理实施及评价

在基于知识管理的信息系统项目管理模式前提下,结合信息系统项目管理中的知识管理实践,集中研究信息系统项目管理的知识管理实施和评价方法,以用于指导信息系统项目管理的知识管理成功实施,进而提高信息系统建设的成功率。     

A Delphi study of knowledge management systems: Scope and requirements

We empirically explored the roles and scope of knowledge management systems in organizations. Building on a knowledge-based view of the firm, we hypothesized and empirically tested our belief that more integration is needed between technologies intended to support knowledge and those supporting business operations. Findings from a Delphi study and in-depth interviews illustrated this and led us to suggest a revised approach to developing organizational knowledge management systems.     

Social relationship and its role in knowledge management systems usage

The KMS has been widely implemented in organizations. However, its availability does not guarantee that employees have been willing to spend time and effort using it. We explored the use of KMS with emphasis on social relationship. Specifically, social capital theory was employed to establish the social relationship construct and its three dimensions: tie strength, shared norms, and trust. By studying a company that had implemented a KMS, we explored the dimensions of social relationship and its importance in the use of a KMS by employees. A theoretical framework was used to depict the antecedents of employee's usage behavior. Implications for both researchers and practitioners are discussed, especially for companies expecting to exploit knowledge sharing in the Chinese business environment.     

Distributed name management in internet systems: A study of design and performance issues

This paper deals with the problems associated with developing a name management system which will be an integral part of a special type of distributed system, an internet system. An internet system is a software system that provides transparent access to resources and services distributed over a collection of single-site computing systems and local area networks. The responsibilities of an internet name management system (INMS) are to (1) provide the name service that locates named resources and binds resources to locations within the internet and (2) manage the naming information. This work investigates a distributed approach for maintaining the naming information. Various design issues and possible solutions are discussed. In particular, this paper examines several significant factors, including the design of the global name table, the effects of internet communications, name data locality, and the maintenance of replicated name data, and discusses the effects they may have on the performance of internet naming operations. Empirical data collected from an experiment involving a prototype INMS implementation are presented and then used to analyze the effects of the above design factors.     

Supporting management and maintenance of manufacturing knowledge in design automation systems

Many companies base their business strategy on customized products. To enable a high level of product adaptation in an engineer-to-order approach companies invest time and resources to develop design automation systems. Initially, when implementing a design automation system, the focus is on successfully developing a system that generates design variants based on different customer specifications (i.e. the execution of system embedded knowledge and system output). However, in the long run, two important aspects are the management and maintenance of the knowledge that governs the designs. Further, the increasing emphasis on deploying a holistic view of a product’s properties and functions implies an increasing number of life-cycle requirements. The knowledge to adapt the product to fulfil these requirements should also be used and consequently incorporated into the knowledge-base, allowing for correct decisions to be made. In a system for automated variant design, the implications on the product of these life-cycle requirements have to be expressed as algorithms, production rules and/or computational statements to be intertwined with the design calculations. The number of requirements can be significantly large, and the knowledge scattered over different application systems used for the realisation of the design automation system. This makes it difficult to manage and maintain the system as the product life-cycle environment changes and evolves.In this article, the focus is on the requirements related to manufacturing. For that, an approach for the modelling of manufacturing requirements, supporting both knowledge execution and information management, in systems for automated variant design is introduced. The approach has been applied and refined when developing a design automation system in cooperation with a company to demonstrate and verify the approach’s usability.     

Recommender systems for personal knowledge management in collaborative environments

Personal knowledge management (PKM) is different from the traditional centralized knowledge management (KM) modes. The PKM is suitable for distributed collaborative KM environments. This paper makes an explorative study on the PKM, and analyzes various forms of personal knowledge resources in the product development process. Then a model of recommender systems for PKM is proposed for knowledge sharing among members in the collaborative environment. The key function of the PKM recommender systems is to supply potentially useful personal knowledge resources from the sites where these knowledge resources are created to the sites where the members may need the knowledge. The PKM is in a mode of distributed control rather than a mode of centralized control, which is widely used by traditional KM methods and tools. This study paves a way for developing an advanced mode of KM platforms for PKM sharing in collaborative environments.     

Knowledge management systems and organizational knowledge processing challenges: A field experiment

This paper investigates the appropriateness of knowledge management system (KMS) designs for different organizational knowledge processing challenges. Building on the theory of task-technology fit (TTF), we argue that different KMS designs are more effective for different knowledge tasks. An exploratory field experiment was conducted in the context of Internet-based knowledge sharing services to provide empirical support for our hypotheses. The results of our experiment show that a KMS designed to support the goal GENERATE is more appropriate for divergent type knowledge problems because of its affordances for iterative brainstorming processes. Conversely, for convergent type knowledge processing challenges, a KMS with the goal CHOOSE that supports the ability to clarify and to analyze is more effective.     

Numerical uncertainty management in user and student modeling: An overview of systems and issues

A rapidly growing number of user and student modeling systems have employed numerical techniques for uncertainty management. The three major paradigms are those of Bayesian networks, the Dempster-Shafer theory of evidence, and fuzzy logic. In this overview, each of the first three main sections focuses on one of these paradigms. It first introduces the basic concepts by showing how they can be applied to a relatively simple user modeling problem. It then surveys systems that have applied techniques from the paradigm to user or student modeling, characterizing each system within a common framework. The final main section discusses several aspects of the usability of these techniques for user or student modeling, such as their knowledge engineering requirements, their need for computational resources, and the communicability of their results.     

基于知识管理的信息系统项目管理研究

以构建基于知识管理的信息系统项目管理模式为目的，提出了以知识管理为中心的信息系统项目管理领域模型、以知识管理为主导的信息系统项目管理过程模型、以知识为基础的信息系统项目管理组织发展层次模型以及以知识和知识管理为纽带的信息系统项目管理总体框架，用于指导信息系统项目管理实践。     

General framework for distributed knowledge management in mechatronic systems

This paper is concerned with the application of knowledge management on the mechatronic system. First, data, information and knowledge terms have been explained according to their disparities and similarities. Then, knowledge management has been described in general. The Internet—based CNC machining center has been considered and its knowledge management model has been prepared. The model prepared has been analyzed for machining performance of the manufacturing system.     

Barriers and facilitators to the use of knowledge management systems

This paper reports a post-implementation review of usage and user experiences of an electronic information management system (EIM) in a multinational company. The implementation of this system was the first step in the company's programme to achieve effective knowledge management leading to innovative and integrated business solutions. In the context of low levels of usage, users were asked to identify barriers and facilitators to the use of EIM. The resultant list relates to a considerable array of human and organizational issues that the current implementation methodology has failed to address. This failure impedes progress towards effective knowledge management and realization of the associated business advantages. The findings suggest that a 'technology push' approach to knowledge management has serious limitations. The identification of the critical success factors for EIM provides the basis for a change management process that includes development of the knowledge sharing culture needed to enable effective knowledge management.     

Barriers and facilitators to the use of knowledge management systems

This paper reports a post-implementation review of usage and user experiences of an electronic information management system (EIM) in a multinational company. The implementation of this system was the first step in the company's programme to achieve effective knowledge management leading to innovative and integrated business solutions. In the context of low levels of usage, users were asked to identify barriers and facilitators to the use of EIM. The resultant list relates to a considerable array of human and organizational issues that the current implementation methodology has failed to address. This failure impedes progress towards effective knowledge management and realization of the associated business advantages. The findings suggest that a 'technology push' approach to knowledge management has serious limitations. The identification of the critical success factors for EIM provides the basis for a change management process that includes development of the knowledge sharing culture needed to enable effective knowledge management.     

Towards an evaluation framework for knowledge management systems

In this paper we develop an evaluation framework for Knowledge Management Systems (KMS). The framework builds on the theoretical foundations underlying organizational Knowledge Management (KM) to identify key KM activities and the KMS capabilities required to support each activity. These capabilities are then used to form a benchmark for evaluating KMS. Organizations selecting KMS can use the framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KMS portfolio meet the KM needs of the organization. Other applications of the framework are also discussed.