Knowledge Management Systems

2011 ◽  
pp. 442-450 ◽  
Author(s):  
Ronald Maier ◽  
Thomas Hadrich
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Content Management ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Future Trends ◽  
E Learning ◽  
Abstract Level ◽  
State Of Practice ◽  
Content Management Systems

Knowledge management systems (KMSs) are seen as enabling technologies for an effective and efficient knowledge management (KM). However, up to date the term knowledge management system has often been used ambiguously. Examples are its use for specific KM tools, for KM platforms, or for (a combination of) tools that are applied with KM in mind. So far, investigations about the notion of KMS remain on the abstract level of what a KMS is used for, for example, “a class of information systems applied to managing organizational knowledge” (Alavi & Leidner, 2001, p. 114). The following two sections define the term KMS and obtain a set of characteristics that differentiates KMS from traditional information systems, such as intranet infrastructures, document- and content-management systems, groupware, or e-learning systems. Then, two ideal architectures for KMS are contrasted. It is discussed which KMS architecture fits what type of KM initiatives, and some empirical findings on the state of practice of KMS are summarized. The last sections give an outlook on future trends and conclude the article.

Knowledge Management Systems

2010 ◽  
pp. 779-790 ◽  
Author(s):  
Ronald Maier ◽  
Thomas Hadrich
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Content Management ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Future Trends ◽  
E Learning ◽  
Abstract Level ◽  
State Of Practice ◽  
Content Management Systems

Knowledge management systems (KMSs) are seen as enabling technologies for an effective and efficient knowledge management (KM). However, up to date the term knowledge management system has often been used ambiguously. Examples are its use for specific KM tools, for KM platforms, or for (a combination of) tools that are applied with KM in mind. So far, investigations about the notion of KMS remain on the abstract level of what a KMS is used for, for example, “a class of information systems applied to managing organizational knowledge” (Alavi & Leidner, 2001, p. 114). The following two sections define the term KMS and obtain a set of characteristics that differentiates KMS from traditional information systems, such as intranet infrastructures, document- and content-management systems, groupware, or e-learning systems. Then, two ideal architectures for KMS are contrasted. It is discussed which KMS architecture fits what type of KM initiatives, and some empirical findings on the state of practice of KMS are summarized. The last sections give an outlook on future trends and conclude the article.

Knowledge Management Systems

2011 ◽  
pp. 541-552 ◽  
Author(s):  
Ronald Maier ◽  
Thomas Hadrich
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Content Management ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Future Trends ◽  
E Learning ◽  
Abstract Level ◽  
State Of Practice ◽  
Content Management Systems

Knowledge management systems (KMSs) are seen as enabling technologies for an effective and efficient knowledge management (KM). However, up to date the term knowledge management system has often been used ambiguously. Examples are its use for specific KM tools, for KM platforms, or for (a combination of) tools that are applied with KM in mind. So far, investigations about the notion of KMS remain on the abstract level of what a KMS is used for, for example, “a class of information systems applied to managing organizational knowledge” (Alavi & Leidner, 2001, p. 114). The following two sections define the term KMS and obtain a set of characteristics that differentiates KMS from traditional information systems, such as intranet infrastructures, document- and content-management systems, groupware, or e-learning systems. Then, two ideal architectures for KMS are contrasted. It is discussed which KMS architecture fits what type of KM initiatives, and some empirical findings on the state of practice of KMS are summarized. The last sections give an outlook on future trends and conclude the article.

Stages of Information Systems in E-Government for Knowledge Management

2011 ◽  
pp. 270-280
Author(s):  
Petter Gottschalk
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Police Officers ◽  
Growth Models ◽  
Knowledge Work ◽  
Management Systems ◽  
Financial Crime ◽  
Knowledge Management Systems ◽  
Knowledge Intensive ◽  
Direction Information

A stage model for knowledge management systems in policing financial crime is developed in this chapter. Stages of growth models enable identification of organizational maturity and direction. Information technology to support knowledge work of police officers is improving. For example, new information systems supporting police investigations are evolving. Police investigation is an information-rich and knowledge-intensive practice. Its success depends on turning information into evidence. This chapter presents an organizing framework for knowledge management systems in policing financial crime. Future case studies will empirically have to illustrate and validate the stage hypothesis developed in this paper.

Semantic Integration of Structured and Unstructured Data in Data Warehousing and Knowledge Management Systems

2011 ◽  
pp. 81-105
Author(s):  
Liane Haak
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Data Warehousing ◽  
Semantic Integration ◽  
Unstructured Data ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Application Area ◽  
Ontology Integration ◽  
Basic Ideas

Nowadays, increasing information in enterprises demands new ways of searching and connecting the existing information systems. This chapter describes an approach for the integration of structured and unstructured data focusing on the application to Data Warehousing (DW) and Knowledge Management (KM). Semantic integration is used to improve the interoperability between two well-known and established information systems in the business context of nowadays enterprises. The objective is to introduce a semantic solution in the field of Business Intelligence based on ontology integration. The main focus of this chapter is not to provide a complete literature review of all existing approaches or just to point put the motivation for such an approach. In fact, it presents, under consideration of the most important research approaches, a solution for how a Semantic Integration could be technically achieved in this specific application area. After pointing out the motivation, a short introduction to Semantic Integration, the problems and challenges occurring from it, and the application area of Knowledge Management and Data Warehousing are given. Besides the basic ideas of ontologies and ontology integration are introduced. The approach itself starts with a short overview on the determined requirements, followed by a concept for generating an ontology from a Data Warehouse System (DWS) to be finally integrated with Knowledge Management Systems (KMS) ontology. Finally SENAGATOR, an exemplarily system for semantic navigation based on integrated ontologies, is shortly introduced.

Learning Object Evaluation

2010 ◽  
pp. 800-807
Author(s):  
Erla M. Morales ◽  
Francisco J. García ◽  
Ángela Barrón
Keyword(s):  
Knowledge Management ◽  
Academic Research ◽  
Learning Object ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
E Learning

One of the biggest challenges to knowledge management systems (KMS) is the great importance that many organizations have given to obtaining information rather than to its retrieval. As a result, users face the problem of having large quantities of information and many difficulties retrieving the information they really need. Through an e-learning repository we can find a myriad of content from academic research and contributions, but how to guarantee and manage their content’s quality?

MEASURING THE CONTRIBUTIONS OF KNOWLEDGE MANAGEMENT SYSTEMS TO THE STRATEGIC COMPETITIVENESS OF ORGANIZATIONS: A REVIEW AND A MODEL

2010 ◽  
Vol 07 (02) ◽  
pp. 89-107 ◽  
Author(s):  
ELIE GEISLER
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Absorptive Capacity ◽  
Knowledge Systems ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Multi Stage ◽  
Intermediate Outcomes ◽  
Stage Process ◽  
The Relationship

Why and how do Knowledge Management Systems (KMS) contribute to the strategic competitiveness of organizations? This paper reviews the literature and proposes a model in which KMS is viewed from three different perspectives: (1) crucial resource; (2) driver of absorptive capacity; and (3) innovation adopted by the organization. The paper critiques the method used by KMS researchers whereby co-variation of KMS and competitiveness is utilized to study the relationship between these variables. The model proposed here is a multi-stage process. The successful use of KMS generates intermediate outcomes that in turn impact the organization and produces improved strategic competitiveness. The different approaches to KMS and the stage-process allow for the unique attributes of knowledge systems, different from information systems. The advantages and limitations of the model are discussed.

Ontology

2017 ◽  
pp. 79-102
Author(s):  
Syed Raiyan Ghani
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Information Systems ◽  
Cognitive Process ◽  
Information Overload ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Library Users

Library requires mighty technologies to support, sort and categorize information in the shortest span of time for better knowledge-tasks and decision-making. Ontology is one of the needs and adroitness which helps library users in acquiring better standardized vocabulary, better routes and better search. The chapter discusses how ontology libraries can process as a connection in modifying versatile users and diligence to reveal, judge, utilize, and disseminate the information overload. The Ontology–based Information Systems (IS) and Knowledge Management Systems (KMS) helps cognitive process of reaching a decision which are used to draw out user information and fuzzy ontologies are applied to store the accumulated knowledge.

Back to the future of Knowledge Management Systems off the beaten paths

2020 ◽  
Vol 58 (9) ◽  
pp. 1953-1984
Author(s):  
Roberto Cerchione ◽  
Piera Centobelli ◽  
Pierluigi Zerbino ◽  
Amitabh Anand
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Knowledge Translation ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Collaborative Relationships ◽  
Content Type ◽  
Research Questions ◽  
Forms Of Knowledge

PurposeThe evolution of Knowledge-Management (KM)-related literature has highlighted that Knowledge Management Systems (KMSs) have undergone massive changes in collaborative environments. Information-Systems-enabled KM seems to be the necessary response to the recent challenges posed by globalisation and technology dynamics to both large companies (LCs) and small and medium enterprises (SMEs).Design/methodology/approachThis paper provides a systematic review about KMSs to offer an analytical overview of their role in supporting innovative forms of knowledge translation occurring in collaborative relationships. A sample of 129 papers was selected and analysed according to three perspectives: unit of analysis (LCs, SMEs), phases of the KM process (adoption, translation) and topic area (KM Practices, KM Tools, KMSs).FindingsThe findings highlight five literature gaps: (1) the role of KM practices supporting knowledge translation; (2) the impact of the alignment among KM practices, firm's complexity, dimension and culture on KM process; (3) the effect of KM tools on knowledge translation; (4) the variety of KMSs exploited in both LCs and SMEs; and (5) the alignment between organisational structure and information systems in KM context. Accordingly, 13 research questions were formulated.Originality/valueThe proposed research questions define a formal research agenda that could steer further research efforts about the KMS topic for improving the body of knowledge in the KM field. Scientific literature is currently lacking a contribution assessing the role of KMSs in supporting innovative forms of knowledge translation that occur in collaborative relationships.

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