Knowledge Patterns and Knowledge Refactorings for Increasing the Quality of Knowledge

2011 ◽  
pp. 281-328 ◽  
Author(s):  
Jörg Rech ◽  
Raimund L. Feldmann ◽  
Eric Ras
Keyword(s):  
Knowledge Management ◽  
Software Engineering ◽  
Management Systems ◽  
Technical Knowledge ◽  
Knowledge Management Systems ◽  
Body Of Knowledge ◽  
Management Knowledge ◽  
Knowledge Industry ◽  
Industry Standards

Knowledge management is a relatively young discipline. It has accumulated a valuable body-of-knowledge on how to structure and represent knowledge, or how to design socio-technical knowledge management systems. A wide variety of approaches and systems exist that are often not interoperable, and hence, prevent an easy exchange of the gathered knowledge. Industry standards, which have been accepted and are in widespread use are missing, as well as general concepts to describe common, recurring patterns of how to describe, structure, interrelate, group, or manage knowledge elements. In this chapter, we introduce the concepts “knowledge pattern” and “knowledge anti-pattern” to describe best and worst practices in knowledge management, “knowledge refactoring” to improve or change knowledge antipatterns, and “quality of knowledge” to describe desirable characteristics of knowledge in knowledge management systems. The concepts are transferred from software engineering to the field of knowledge management based on our experience from several knowledge management projects.

Effort-Accuracy Trade-Off in Using Knowledge Management Systems

2010 ◽  
pp. 2226-2252
Author(s):  
Robin S. Poston ◽  
Cheri Speier
Keyword(s):  
Knowledge Management ◽  
Research Study ◽  
Management Systems ◽  
Future Research ◽  
Cognitive Resources ◽  
Knowledge Management Systems ◽  
Trade Off ◽  
Content Quality ◽  
Computer Mediated

To solve complicated problems, people often seek input from others. Knowledge management systems (KMSs) provide help in this activity by offering a computer-mediated approach to information sharing. However, if the KMS contains content that is obsolete or incomplete, those using the system may expend greater amounts of effort to detect what content is worthwhile or they risk relying on poor inputs, which may lead to less accurate solutions to their problems. As a result, most KMSs include rating schemes as part of the user interface designed to help those using the system identify high-quality content. Rating schemes depend on current users rating the quality of the existing content, guiding subsequent users in future content searches. If specific ratings are low in validity, then they may not reflect the true content quality (unintentionally or intentionally). This chapter provides a robust summary of the KMS literature and draws on the effort-accuracy trade-off framework to offer the results of a research study. The research study examines how rating validity influences how KMS users employ their limited cognitive resources to search and evaluate KMS content, with the goal of finding and using the highest-quality content. Through an experimental design, the study described herein manipulates rating validity and content quality in a replicated KMS setting and examines how users trade off search and evaluation effort. The results of the study demonstrate that rating validity differentially influences how KMS search and evaluation effort relates to decision accuracy. The chapter concludes with a discussion of the study findings and ideas for future research.

Qualitative Analysis of Semantically Enabled Knowledge Management Systems in Agile Software Engineering

2012 ◽  
pp. 144-164
Author(s):  
Jörg Rech ◽  
Christian Bogner
Keyword(s):  
Knowledge Management ◽  
Software Engineering ◽  
Qualitative Analysis ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Two Phase ◽  
Complex Processes ◽  
Management Processes ◽  
Agile Software Engineering ◽  
Agile Software

In many agile software engineering organizations there is not enough time to follow knowledge management processes, to retrieve knowledge in complex processes, or to systematically elicit knowledge. This chapter gives an overview about the human-centered design of semantically-enabled knowledge management systems based on Wikis used in agile software engineering environments. The methodology – developed in the RISE (Reuse in Software Engineering) project – enables and supports the design of human-centered knowledge sharing platforms, such as Wikis. Furthermore, the paper specifies requirements one should keep in mind when building human-centered systems to support knowledge management. A two-phase qualitative analysis showed that the knowledge management system acts as a flexible and customizable view on the information needed during working-time which strongly relieves software engineers from time-consuming retrieval activities. Furthermore, the observations gave some hints about how the software system supports the collection of vital working experiences and how it could be subsequently formed and refined.

scholarly journals Effectiveness of the Partial Implementation of a Cloud-Based Knowledge Management System

2020 ◽  
Vol 15 (13) ◽  
pp. 155
Author(s):  
Zhi-Qin Liu ◽  
Evgenij Dorozhkin ◽  
Nataliia Davydova ◽  
Nadezhda Sadovnikova
Keyword(s):  
Cloud Computing ◽  
Knowledge Management ◽  
Management System ◽  
Cloud Services ◽  
Knowledge Management System ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Computing Technologies ◽  
Partial Implementation

Nowadays cloud computing technologies are cost-effective services enabling to generate the learning quality. The goal of this research is to define the borderline of the effectiveness and limitation of the partial implementation of Knowledge Management System based on cloud computing technologies. In view of this, the research in the form of knowledge testing as well as objective and subjective assessment of the learning quality within a wide sampling of 396 students in two independent reference groups was conducted. One of the groups has used traditional methods of the training conducted in classrooms by applying e-learning, and the other one has used the Knowledge Management System based on cloud services under the most budgetary option. As a result, a range of certain differences in the quality of training of two groups was found out and the latter must be used for a further study. According to the results of all tests related to the quality of training, in the group, that has used Knowledge Management Systems and cloud computing technologies, the students have demonstrated results above average in various tests than in the group where these technologies have not been used. The results allow defining specific advanced features of Knowledge Management Systems with the application of cloud computing technologies in the education.

Exploring System Use as a Measure of Knowledge Management Success

2010 ◽  
pp. 63-77
Author(s):  
Murray E. Jennex
Keyword(s):  
Knowledge Management ◽  
Management System ◽  
Knowledge Management System ◽  
Management Systems ◽  
Intention To Use ◽  
Knowledge Management Systems ◽  
Success Model ◽  
System Use ◽  
System Success

This article discusses system use as a measure of knowledge management success. It is proposed that for knowledge management systems (KMS) it is not the amount of use that is important, but rather the quality of that use and the intention to use the KMS when appropriate. Evidence is provided to support this proposition and a knowledge management system success model incorporating this proposition is discussed. Additionally, findings are provided that show that new users to an organization use the KMS differently than experienced users and implications of this difference are discussed.

Assessing Knowledge Management Systems Usage in Supporting Decision Making Processes in Organizations

2014 ◽  
pp. 326-340 ◽  
Author(s):  
Mahmoud Abdelrahman ◽  
K. Nadia Papamichail ◽  
Simon French
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Knowledge Economy ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Critical Factors ◽  
Public And Private ◽  
Decision Making Processes ◽  
Support Decision Making

With the advent of the knowledge economy and the growing importance of knowledge societies, organizations are constantly seeking new ways of leveraging knowledge assets to support Decision Making (DM) processes. This chapter presents an initial insight to the little-researched phenomenon of how Knowledge Management Systems (KMSs) can support DM processes in organizations. A synthesis of ideas from a literature review suggests a new conceptual framework with several critical factors that organizations should take into account to assess the usage of KMSs tools in supporting DM processes in organizations. The proposed framework, “USUQ,” will benefit managers in both public and private sectors in knowing how the Usage, Satisfaction, Usefulness, and the Quality of using KMSs can support DM processes.

scholarly journals Effect of Cloud Computing Systems in Terms of Service Quality of Knowledge Management Systems

2016 ◽  
Vol 4 (1) ◽  
pp. 73-76 ◽  
Author(s):  
Hamed Rezaei ◽  
◽  
Behdad Karimi ◽  
Seyed Jamalodin Hosseini ◽  
◽  
...  
Keyword(s):  
Cloud Computing ◽  
Knowledge Management ◽  
Service Quality ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Computing Systems

Effort-Accuracy Trade-Off in Using Knowledge Management Systems

2010 ◽  
pp. 1-27
Author(s):  
Robin S. Poston ◽  
Cheri Speier
Keyword(s):  
Knowledge Management ◽  
Research Study ◽  
Management Systems ◽  
Future Research ◽  
Cognitive Resources ◽  
Knowledge Management Systems ◽  
Trade Off ◽  
Content Quality ◽  
Computer Mediated

To solve complicated problems, people often seek input from others. Knowledge management systems (KMSs) provide help in this activity by offering a computer-mediated approach to information sharing. However, if the KMS contains content that is obsolete or incomplete, those using the system may expend greater amounts of effort to detect what content is worthwhile or they risk relying on poor inputs, which may lead to less accurate solutions to their problems. As a result, most KMSs include rating schemes as part of the user interface designed to help those using the system identify high-quality content. Rating schemes depend on current users rating the quality of the existing content, guiding subsequent users in future content searches. If specific ratings are low in validity, then they may not reflect the true content quality (unintentionally or intentionally). This chapter provides a robust summary of the KMS literature and draws on the effort-accuracy trade-off framework to offer the results of a research study. The research study examines how rating validity influences how KMS users employ their limited cognitive resources to search and evaluate KMS content, with the goal of finding and using the highest-quality content. Through an experimental design, the study described herein manipulates rating validity and content quality in a replicated KMS setting and examines how users trade off search and evaluation effort. The results of the study demonstrate that rating validity differentially influences how KMS search and evaluation effort relates to decision accuracy. The chapter concludes with a discussion of the study findings and ideas for future research.

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