This chapter introduces and reviews the concept of distributed knowledge management within the Healthcare environment and between Healthcare and other partner organisations. As management should not be mistaken for control, distributed should not be identified with multicentered. Trade-offs between managerial centralism and social contextuality should be allowed. Although the core issues in knowledge management are not technological, tools that can support the central versus social dualism of knowledge management are critical to the effective and appropriate use of generated knowledge. Information tools can significantly affect the user experience and local social wiliness to participation and enhance the managerial trends that make use of knowledge networks and shared logistics. They include service-oriented architectures (SOA), artificial intelligence networks (AIN), multiple agent systems (MAS) and the contextual tools of Web 2.0. All of those tools feed their functionality on the semantic detail, the granularity and the trust levels enjoyed by their information sources.
Key Terms in this Chapter
Computer Agents: A program that performs some information gathering or processing task in the background. Typically, an agent is given a very small and well-defined task. Although the theory behind agents has been around for some time, agents have become more prominent with the growth of the Internet. Many companies now sell software that enables you to configure an agent to search the Internet for certain types of information.
Distributed Knowledge Management System (DKMS): A DKMS is a system that manages the integration of distributed objects into a functioning whole producing, maintaining, and enhancing a business knowledge base. A business knowledge base is the set of data, validated models, meta-models, and software used for manipulating these, pertaining to the enterprise, produced either by using a DKMS, or imported from other sources upon creation of a DKMS. A DKMS, in this view, requires a knowledge base to begin operation. But it enhances its own knowledge base with the passage of time because it is a self-correcting system, subject to testing against experience. The DKMS must not only manage data, but all of the objects, object models, process models, use case models, object interaction models, and dynamic models, used to process data and to interpret it to produce a business knowledge base.
Contextual Knowledge: Knowledge in context, information, and/or skills that have particular meaning because of the conditions that form part of their description.
Organisational Knowledge: The capability, which members of an organization developed, to draw distinctions in the process of carrying out their work, in particular concrete contexts, by enacting sets of generalisations whose application depends on historically evolved collective understanding.
Complete Chapter List
Athina A. Lazakidou
Athina A. Lazakidou
Sanjay P. Sood, Sandhya Keeroo, Victor W.A. Mbarika, Nupur Prakash, Ankur Seth
Ana Ferreira, Ricardo Cruz-Correia, Luís Antunes, David Chadwick
Graham D. Bodie, Mohan J. Dutta, Ambar Basu
Isabel de la Torre Díez
Roger Tait, Gerald Schaefer
Bill Ag. Drougas
Tammara Massey, Foad Dabiri, Roozbeh Jafari, Hyduke Noshadi, Philip Brisk, Majid Sarrafzadeh
Anton V. Vladzymyrskyy
Cheon-Pyo Lee, J. P. Shim
Rafael Capilla, Alfonso del Río, Miguel Ángel Valero, José Antonio Sánchez
José Antonio Seoane Fernández, Juan Luis Pérez Ordóñez, Noha Veiguela Blanco
I. Apostolakis, A. Chryssanthou, I. Varlamis
Maria Andréia F. Rodrigues
Tiffany A. Koszalka, Bradley Olson
Anastasia N. Kastania, Stelios Zimeras
Bill Ag Drougas, Maria Sevdali
Mary Schmeida, Ramona McNeal