Systems Thinking
© Copyright Carter McNamara, MBA, PhD, Authenticity Consulting, LLC. Adapted from the Field Guide to Consulting and Organizational Development and Field Guide to Consulting and Organizational Development with Nonprofits. Three of the biggest breakthroughs in how we understand and successfully guide changes in ourselves, others and organizations are systems theory, systems thinking and systems tools. To understand how they are used, we first must understand the concept of a system. Sections of This Topic Include Basics -- Definitions - - - What's a System? Also seeRelated Library Topics Also See the Library's Blogs Related to Systems Theory, Chaos Theory and Systems Thinking In addition to the articles on this current page, also see the following blogs that have posts related to Systems Theory, Chaos Theory and Systems Thinking . Definitions: Systems, Systems Theory, Systems Thinking, Tools What's a System? Systems range from simple to complex. A pile of sand is not a system. Personal Mastery
What is KM? Knowledge Management Explained
Knowledge Management, (KM) is a concept and a term that arose approximately two decades ago, roughly in 1990. Quite simply one might say that it means organizing an organization's information and knowledge holistically, but that sounds a bit wooly, and surprisingly enough, even though it sounds overbroad, it is not the whole picture. Very early on in the KM movement, Davenport (1994) offered the still widely quoted definition: "Knowledge management is the process of capturing, distributing, and effectively using knowledge." This definition has the virtue of being simple, stark, and to the point. "Knowledge management is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise's information assets. Both definitions share a very organizational, a very corporate orientation. From: Tom Short, Senior consultant, Knowledge Management, IBM Global Services Explicit, Implicit and Tacit Knowledge So what is involved in KM?
Knowledge engineering
Knowledge engineering (KE) was defined in 1983 by Edward Feigenbaum, and Pamela McCorduck as follows: KE is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise.[1] It is used in many computer science domains such as artificial intelligence,[2][3] including databases, data mining, bioinformatics, expert systems, decision support systems and geographic information systems. Various activities of KE specific for the development of a knowledge-based system: Assessment of the problemDevelopment of a knowledge-based system shell/structureAcquisition and structuring of the related information, knowledge and specific preferences (IPK model)Implementation of the structured knowledge into knowledge basesTesting and validation of the inserted knowledgeIntegration and maintenance of the systemRevision and evaluation of the system. Knowledge engineering principles[edit] Bibliography[edit]
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Collaborative network
A collaborative network, is a network consisting of a variety of entities (e.g. organizations and people) that are largely autonomous, geographically distributed, and heterogeneous in terms of their operating environment, culture, social capital and goals, but that collaborate to better achieve common or compatible goals, and whose interactions are supported by computer networks. The discipline of collaborative networks focuses on the structure, behavior, and evolving dynamics of networks of autonomous entities that collaborate to better achieve common or compatible goals.[1][2] There are several manifestations of collaborative networks, e.g.:[1] Virtual enterprise (VE).Virtual Organization (VO).Dynamic Virtual Organization.Extended Enterprise.VO Breeding environment (VBE).Professional virtual community (PVC).Business Ecosystem.Virtual manufacturing network Applications[edit] Elements[edit] The seven essential elements of collaborative networks: Reference models[edit] Challenges[edit]
Journal of Knowledge Management Practice: Library
Journal of Knowledge Management Practice Editorial TLA welcomes you to its unique experiment in journal publishing - the open library concept - pioneered by TLA in 1998. In this approach you the reader have open access to all articles that have been, and are currently being, published in JKMP by TLA. Please note that the articles have been optimised for viewing using Internet Explorer. I think of this open library concept as a "knowledge garden". Note that articles originating prior to August 1999 were published in the Journal of Systemic Knowledge Management. If you are pleased with what you see in JKMP, please visit us on FaceBook and Comment &/or Like. Peter A.C. In The Knowledge Garden: Volume 1: 1998 - 1999 Volume 2: 2000 - 2001 Volume 3: 2002 Volume 4: 2003 Volume 5: 2004 Volume 6: 2005 Vol. 7, No. 1, March 2006 Vol. 7, No. 2, June 2006 Vol. 7, No. 3, September 2006 Vol. 7, No. 4, December 2006 Vol. 8, No. 1, March 2007 Vol. 8, SI-1, May 2007 Vol. 8, No. 2, June 2007 Vol. 8, No. 3, September 2007
Open innovation
Open innovation is a term promoted by Henry Chesbrough, adjunct professor and faculty director of the Center for Open Innovation at the Haas School of Business at the University of California,[1] in a book of the same name,[2] though the idea and discussion about some consequences (especially the interfirm cooperation in R&D) date as far back as the 1960s[citation needed]. Some instances of open innovation are Open collaboration,[3] a pattern of collaboration, innovation, and production. The concept is also related to user innovation, cumulative innovation, know-how trading, mass innovation and distributed innovation. “Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology”.[2] Alternatively, it is "innovating with partners by sharing risk and sharing reward. Advantages[edit] Disadvantages[edit] Models of open innovation[edit] See also[edit]
A - Knowledge Translation at the Canadian Institutes of Health Research
TECHNICAL BRIEF NO. 18 2007 PDF version Jacqueline Tetroe, MA Senior Policy Analyst, Knowledge Translation Portfolio About the Canadian Institutes of Health Research The Canadian Institutes of Health Research (CIHR) is the major federal agency responsible for funding health research in Canada. It aims to excel in the creation of new health knowledge and to translate that knowledge from the research setting into real-world applications. CIHR consists of 13 "virtual" institutes, each headed by a scientific director and assisted by an institute advisory board. The work of the institutes embraces the four pillars of health research: (1) biomedical; (2) clinical; (3) health systems and services; and (4) population and public health. Knowledge Translation at CIHR: Definitions, Purpose, and Rationale for Knowledge Translation CIHR's definition of knowledge translation (KT) has been cited and adapted widely. Context for the CIHR Definition But What Does KT Really Mean? Knowledge to Action Table 1.
