Centralized versus peer-To-peer knowledge management systems

The term knowledge management system (KMS) has been used widely to denote information and communication technologies in support of knowledge management. However, so far investigations about the notion of KMS, their functions and architecture as well as the differ-ences to other types of systems remain on an abstract level. This paper reviews the literature on KMS and distills a number of characteristics concerning the specifics of knowledge to be managed, the platform metaphor, advanced services, KM instruments, supported processes, participants and goals of their application. The paper then presents two ideal architectures for KMS, a centralized and a peer-to-peer architecture, discusses their differences with the help of two example systems and suggests that each of these architectures fits a different type of KM initiative. Copyright #2006 John Wiley & Sons, Ltd.

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& Research Article Centralized Versus Peer-to-Peer Knowledge Management Systems Ronald Maier* and Thomas Ha¨drich Department of Management Information Systems And OR, Martin-Luther-University Halle-Wittenberg, Germany The term knowledge management system (KMS) has been used widely to denote information and communication technologies in support of knowledge management. However, so far investigations about the notion of KMS, their functions and architecture as well as the differ- ences to other types of systems remain on an abstract level. This paper reviews the literature on KMS and distills a number of characteristics concerning the specifics of knowledge to be managed, the platform metaphor, advanced services, KM instruments, supported processes, participants and goals of their application. The paper then presents two ideal architectures for KMS, a centralized and a peer-to-peer architecture, discusses their differences with the help of two example systems and suggests that each of these architectures fits a different type of KM initiative. Copyright # 2006 John Wiley & Sons, Ltd. MOTIVATION Knowledge management (KM) has been discussed intensively from a human-oriented and from a technology-oriented perspective. Knowledge man- agement systems are seen as enabling technologies for an effective and efficient KM. However, up- to-date the term knowledge management system (KMS) is often vaguely defined and used ambigu- ously. Examples are its use for specific KM tools, for KM platforms or for a combination of tools that are applied with KM in mind. It remains unclear what separates KMS from other types of systems that are also discussed as supporting KM initiatives. Examples are Intranet infrastructures, document and content management systems, artifi- cial intelligence technologies, business intelligence tools, visualization tools, Groupware or e-learning systems. So far, investigations about the notion of KMS remain on the abstract level of what a KMS is used for, e.g. ‘a class of information systems applied to managing organizational knowledge’ (Alavi and Leidner, 2001, p. 114), and do not answer the question whether a concrete tool or sys- tem qualifies as a KMS or, in other words, what ser- vices a KMS has to offer. A general frame of reference in the sense of a system architecture is needed for the analysis of existing tools and sys- tems as well as for the development of individual KMS solutions. Goals of this paper are to define the term KMS and to obtain a set of characteristics that differenti- ate KMS from other types of systems (section 2), to contrast two ideal architectures for KMS which are amalgamated on the basis of KMS architectures proposed in the literature and to discuss the state-of-the-art with the help of example systems offered on the market (section 3) as well as to dis- cuss the differences between the architectures and which KMS architecture fits what type of KM initiative (section 4). TOWARDS A DEFINITION OF KNOWLEDGE MANAGEMENT SYSTEMS Even though there is considerable disagreement in the literature and business practice about what exactly KM is, there are a number of researchers Knowledge and Process Management Volume 13 Number 1 pp 47–61 (2006) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/kpm.244 Copyright # 2006 John Wiley & Sons, Ltd. *Correspondence to: Ronald Maier, Department of Management Information Systems And OR, Martin-Luther-University Halle-Wittenberg, Germany. E-mail: ronald.maier@wiwi.uni-halle.de and practitioners who stress the importance and usefulness of KMS as enabler or vehicle for the implementation of these approaches. A review of the literature on information and communication technologies (ICT) to support KM reveals a number of different terms in use, such as knowledge ware- house, KM software, suite, (support) system, tech- nology or organizational memory (information) system (e.g. Alavi and Leidner, 2001; Nedeß and Jacob, 2000; Maier, 2004, p. 79ff; McDermott, 1999, p. 104; Mentzas et al., 2001, p. 95f; Seifried and Eppler, 2000; Stein and Zwass, 1995, p. 98). In addi- tion to these terms meaning a comprehensive plat- form in support of KM, many authors provide more or less extensive lists of individual tools or technologies that can be used to support KM initia- tives as a whole or certain processes, life cycle phases or tasks thereof (e.g. Allee, 1997, p. 224f; Binney, 2001, p. 37ff; Borghoff and Pareschi, 1998, p. 5f; Hoffmann, 2001, p. 78f; Jackson, 2003, p. 5f; Meso and Smith, 2000, p. 227ff; Ruggles, 1998, p. 82ff). Apart from these terms with a clear focus on KM or organizational memory, there is another group of software systems that supports these approaches called e-learning suite, learning management plat- form, portal, suite or system (Maier, 2004, p. 81). These platforms not only support presentation, administration and organization of teaching mate- rial, but also interaction between and among tea- chers and students (Astleitner and Schinagl, 2000, p. 114). KMS with roots in document management, collaboration or Groupware and learning manage- ment systems with roots in computer-based train- ing already share a substantial portion of functionality and seem to converge or at least be integrated with each other. Recently, the terms KM tools or KMS have gained wide acceptance both in the literature and on the market. Conse- quently, we use the term KMS being well aware that there are a number of similar conceptualiza- tions that complement the functionality and archi- tectures of KMS. In the following, we will summarize the most important characteristics of KMS as can be found in the literature. Goals Goals are defined by the KM initiative in which the KMS is deployed. Stein/Zwass define organiza- tional memory information system as ‘a system that functions to provide a means by which knowl- edge from the past is brought to bear on present activities, thus resulting in increased levels of effec- tiveness for the organization‘ (Stein and Zwass, 1995, p. 95; for organizational effectiveness e.g. Lewin and Minton, 1998). This definition stresses the primary goal of KMS as to increase organiza- tional effectiveness by a systematic management of knowledge. Thus, KMS are the technological part of a KM initiative that also comprises per- son-oriented and organizational instruments tar- geted at improving productivity of knowledge work (Maier, 2004, p. 44ff, 55). KM initiatives can be classified according to strategy in human- oriented, personalization initiatives and technol- ogy-oriented codification initiatives (Hansen et al., 1999). They can further be distinguished according to scope into enterprise-specific initiatives and initiatives that cross organizational boundaries. According to organizational design, the initiative can establish a central organizational unit responsi- ble for KM or it can be a decentral initiative run by a number of projects and/or communities. The initiative can focus on a certain type of content along the knowledge life cycle e.g. ideas, experi- ences, lessons learned, approved knowledge pro- ducts, procedures, best practices or patents. Finally, the organizational culture of the company or organization in which the KM initiative is started, can be characterized as open, trustful, col- lective where willingness to share knowledge is high or as confidential, distrustful, individual, with high barriers to knowledge sharing (see Maier, 2004, p. 404ff for a definition of and empiri- cal results about this typology of KM initiatives). The type of initiative determines the type of infor- mation system for its support which can be regarded as a KMS from the perspective of its application environment. Processes KMS are developed to support and enhance knowl- edge-intensive processes, tasks or projects (Detlor, 2002, p. 200; Jennex and Olfmann, 2003, p. 214) of e.g. knowledge creation, organization, storage, retrie- val, transfer, refinement and packaging, (re-)use, revision and feedback, also called the knowledge life cycle, ultimately to support knowledge work (Davenport et al., 1996, p. 54). In this view, KMS pro- vide a seamless pipeline for the flow of explicit knowledge through a refinement process (Zack, 1999, p. 49), or a thinking forum containing interpre- tations, half-formed judgements, ideas and other perishable insights that aims at sparking collabora- tive thinking (McDermott, 1999, p. 112). Comprehensive platform Whereas the focus on processes can be seen as a user-centric approach, an IT-centric approach RESEARCH ARTICLE Knowledge and Process Management 48 R. Maier and T. Ha¨drich provides a base system to capture and distribute knowledge (Jennex and Olfmann, 2003, p. 215). This platform is then used throughout the organi- zation. In this case, the KMS is not an application system targeted at a single KM initiative, but a plat- form that can either be used as-is to support knowl- edge processes or that is used as the integrating base system and repository on which KM applica- tion systems are built. Comprehensive in this case means that the platform offers extensive functional- ity for user administration, messaging, conferen- cing and sharing of (documented) knowledge, i.e. publication, search, retrieval and presentation. Advanced services KMS are described as ICT platforms on which a number of integrated services are built. The pro- cesses that have to be supported give a first indica- tion of the types of services that are needed. Examples are rather basic services e.g. for colla- boration, workflow management, document and content management, visualization, search and retrieval (e.g. Seifried and Eppler, 2000, p. 31ff) or more advanced services e.g. profiling, personaliza- tion, text analysis, clustering and categorization to increase the relevance of retrieved and pushed information, advanced graphical techniques for navigation, awareness services, shared workspaces, (distributed) learning services as well as integra- tion of and reasoning about various (document) sources on the basis of a shared ontology (e.g. Bair, 1998, p. 2; Borghoff and Pareschi, 1998, p. 5f; Maier, 2004, p. 260ff). KM instruments KMS are applied in a large number of application areas e.g. in product development, process improvement, project management, post-merger integration or human resource management (Tsui, 2003, p. 21). More specifically, KMS support KM instruments e.g. (1) the capture, creation and shar- ing of best practices, (2) the implementation of experience management systems, (3) the creation of corporate knowledge directories, taxonomies or ontologies, (4) expertise locators, yellow and blue pages as well as skill management systems, also called people-finder systems, (5) collaborative fil- tering and handling of interests used to connect people, (6) the creation and fostering of commu- nities or knowledge networks, and (7) the facilita- tion of intelligent problem solving (e.g. Alavi and Leidner, 2001, p. 114; McDermott, 1999, p. 111ff; Tsui, 2003, p. 7). KMS in this case offer a targeted combination and integration of knowledge services that together foster one or more KM instrument(s). Specifics of knowledge KMS are applied to managing knowledge which is described as ‘personalized information [ . . . ] related to facts, procedures, concepts, interpreta- tions, ideas, observations, and judgements’ (Alavi and Leidner, 2001, p. 109, 114). From the perspec- tive of KMS, knowledge is information that is meaningfully organized, accumulated and embedded in a context of creation and application. KMS primarily leverage codified knowledge, but also aid communication or inference used to inter- pret situations and to generate activities, behaviour and solutions. Thus, on the one hand KMS might not appear radically different from existing IS, but help to assimilate contextualized information. On the other hand, the role of ICT is to provide access to sources of knowledge and, with the help of shared context, to increase the breadth of knowl- edge sharing between persons rather than storing knowledge itself (Alavi and Leidner, 2001, p. 111). The internal context of knowledge describes the cir- cumstances of its creation, e.g. the author(s), crea- tion date and circumstances, assumptions or purpose of creation. The external context relates to retrieval and application of knowledge. It cate- gorizes knowledge, relates it to other knowledge, describes access rights, usage restrictions and cir- cumstances as well as feedback from its re-use (Barry and Schamber, 1998, p. 222; Eppler, 2003, p. 125f). Participants Users play the roles of active, involved participants in knowledge networks and communities fostered by KMS. This is reflected by the support of context in KMS. Contextualization is thus one of the key characteristics of KMS (Apitz, et al., 2002) which provide a semantic link between explicit, codified knowledge and participants holding or seeking knowledge in certain subject areas. Context enhances the simple ‘container’ metaphor of orga- nizational knowledge by a network of artefacts and people, of memory and of processing (Ackerman and Halverson, 1998, p. 64). Communities or net- works of knowledge workers that ‘own the knowl- edge’ and decide what and how to share can provide important context for a KMS (McDermott, 1999, p. 108, 111ff). Decontextualization and recon- textualization turn static knowledge objects into knowledge processes (Ackerman and Halverson, 1998, p. 64). Meta-knowledge in a KMS, e.g. in Knowledge and Process Management RESEARCH ARTICLE Centralized Versus Peer-to-Peer Knowledge 49 the form of a set of expert profiles or the content of a skill management system, is sometimes as impor- tant as the original knowledge itself (Alavi and Leidner, 2001, p. 121). Figure 1 gives an overview of these characteris- tics. The KMS is visualized by the triangle. Goals stated by a KM initiative define the KM instru- ments that should be supported by the KMS’s func- tions and control their deployment. Thus, a KMS has to be aligned with the specifics of its applica- tion environment, the types of KM initiative e.g. the strategy, scope, organizational design, type of contents and cultural aspects. Participants and communities or knowledge networks are the tar- geted user groups that interact with the KMS in order to carry out knowledge tasks. The knowledge tasks are organized in acquisition and deployment processes required for the management of knowl- edge. The KMS itself consists of a comprehensive platform rather than individual tools with advanced services built on top that explicitly consider the specifics of knowledge as infor- mation (or content) plus context. The services are combined and integrated in order to foster KM instruments. A definition of the term KMS and a subsequent development of architectures for KMS have to stress these characteristics. Consequently, a KMS is defined as a comprehensive ICT platform for col- laboration and knowledge sharing with advanced services built on top that are contextualized, inte- grated on the basis of a shared ontology and perso- nalized for participants networked in communities. KMS foster the implementation of KM instruments in support of knowledge processes targeted at increasing organizational effectiveness. The characteristics discussed above can be used as requirements in order to judge whether an actual system is a KMS or not. Many systems marketed as KMS have their foundations e.g. in document or content management systems, artificial intelligence technologies, business intelligence tools, Groupware or e-learning systems. These systems are more or less substantially extended with advanced services. Thus, actual implementations of ICT systems cer- tainly fulfill the requirements of an ideal KMS only to a certain degree. Therefore, one might imagine a continuum between advanced KMS and other sys- tems that can partially support KM initiatives. The characteristics discussed in this section can be seen as arguing for a certain set of services. Comprehensive platform requires the inclusion of infrastructure services for storage, messaging, access and security which is built on an extensive set of data and knowledge sources. Specifics of knowledge call for the handling of contextualized information which requires integration services that describe resources pulled together from a variety of sources. Advanced services build on top of these integration services and provide support for KM instruments. These knowledge services have to support the entire set of acquisition and deployment processes. From an ICT perspective, these are services for publishing, collaboration, learning and discovery. The knowl- edge services need to be tailored on the one hand to the individual needs of participants and on the other hand to the requirements of the roles they perform in business processes and projects. This calls for personalization services. Finally, participants might need to access KMS with a host of different appliances and applications for which access services have to offer translations and transformation. These services have to be aligned with each other in architectures for KMS. ARCHITECTURES FOR KNOWLEDGE MANAGEMENT SYSTEMS Architectures play an important role in MIS as blueprints or reference models for corresponding implementations of information systems. The term architecture as used in MIS origins in the scientific discipline architecture and is used in a variety of ways e.g. application architecture, sys- tem architecture, information system architecture and especially software architecture. The analysis of the definitions of KMS discussed above, of case studies of organizations using ICT in support ofFigure 1 Characteristics of KMS RESEARCH ARTICLE Knowledge and Process Management 50 R. Maier and T. Ha¨drich KM and of KM tools and systems offered on the market reveals that there are basically two ideal types of architectures of KMS: centralistic KMS and peer-to-peer KMS. The KMS architectures sug- gested in the following are system architectures that can be used to define a framework useful (1) to classify individual tools and systems with respect to the services they offer, (2) to analyse which services are supported by a standard KMS offered on the market (which is shown in this paper) or (3) as reference architecture that helps to design an organization-specific KMS as a combi- nation of tools and systems already implemented in that organization. Centralistic architecture Many KMS solutions implemented in organiza- tions and offered on the market are centralistic cli- ent-/server solutions (Maier, 2004). Figure 2 shows an ideal layered architecture for KMS that repre- sents an amalgamation of theory-driven (e.g. Apitz et al., 2002, p. 33; Zack, 1999, p. 50), market-oriented (e.g. Applehans et al., 1999; Bach et al., 1999, p. 69, Becker et al., 2002, p. 24) and several vendor-speci- fic architectures (e.g. Hyperwave, Open Text Live- link). The comparison of these architectures reveals that each architecture suggests the establishment of a number of services organized on a number of layers. The architectures suggest between three and five layers that basically all follow the same pattern in that a number of sources has to be inte- grated so that advanced services can be built on top. However, none of the architectures comprises the entire set of layers needed for a KMS that fulfils the characteristics defined in section 2 (for a detailed analysis see Maier, 2004, p. 250ff). For example,
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