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☢️ Knowledge Management

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◥ University. {q} PhD. {t} Themes. {t} KM. Information management. Information management (IM) is the collection and management of information from one or more sources and the distribution of that information to one or more audiences. This sometimes involves those who have a stake in, or a right to that information. Management means the organization of and control over the planning, structure and organisation, controlling, processing, evaluating and reporting of information activities in order to meet client objectives and to enable corporate functions in the delivery of information.

Throughout the 1970s this was largely limited to files, file maintenance, and the life cycle management of paper-based files, other media and records. With the proliferation of information technology starting in the 1970s, the job of information management took on a new light, and also began to include the field of data maintenance. No longer was information management a simple job that could be performed by almost anyone. Information management concepts[edit] Quantified Mind (Project) Good Examples of KM Research. Knowledge Management.

Knowledge Management. Knowledge management (KM) is the process of capturing, developing, sharing, and effectively using organizational knowledge.[1] It refers to a multi-disciplined approach to achieving organisational objectives by making the best use of knowledge.[2] An established discipline since 1991 (see Nonaka 1991), KM includes courses taught in the fields of business administration, information systems, management, and library and information sciences.[3][4] More recently, other fields have started contributing to KM research; these include information and media, computer science, public health, and public policy.[5] Columbia University and Kent State University offer dedicated Master of Science degrees in Knowledge Management.[6][7][8] History[edit] In 1999, the term personal knowledge management was introduced; it refers to the management of knowledge at the individual level.[14] Research[edit] Dimensions[edit] The Knowledge Spiral as described by Nonaka & Takeuchi.

Strategies[edit] Motivations[edit] How Social CEOs Harness Social Media for Knowledge Management. CEOs who learn how to harness the power of social media can greatly improve the flow of information among their employees, while managing shared knowledge with their partners in unexpected new ways. This appealing outcome is fast becoming the norm for a new breed of cutting-edge Social CEOs. The Social CEO is a new term to describe modern chief executives who are actively embracing social media tools. Social media provides an effective way to escape top-heavy management structures and broadly access community knowledge. The main problem here involves how to get needed advice and ideas from functional specialists who are spread out across various project teams. One decentralized way to gather knowledge from throughout an organization involves the adoption of internal crowdsourcing software. Crowdsourcing provides a vehicle to produce fresh ideas and insights that will yield a competitive advantage.

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. A few years later, the Gartner Group created another second definition of KM, which is perhaps the most frequently cited one (Duhon, 1998): "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. What is Knowledge Management?

Knowledge Management: An Introduction. Gartner - Knowledge Management (KM) What is difference between DSS and knowledge management systems? The division between the DSS and KMS is a somewhat poorly defined one, and seems to be getting less clear as time goes on and systems incorporate allied functions, BUT the heart of their difference lies in their respective intents... A Knowledge Management System is generally focused on capturing, organizing (and, in that sense, relating) information and on retrieving it and delivering it as needed by the user community. A Decision Support System is focused on using the relationships between stored data, information, or knowledge to present derivative information useful for management, operation, or other decision-based tasks. Capturing Organizational Memory. By E. Jeffrey Conklin, PhD Copyright © 1996 Group Decision Support Systems, Inc.

All rights reserved. Contemporary organizations have only a weak ability to remember and learn from the past, and are thus seeking to gain the capacity for "organizational memory. " By "organizational memory" I mean the record of an organization that is embodied in a set of documents and artifacts. Most organizations currently function within the "artifact-oriented" paradigm (see Figure 1), in which the only thing captured is the stuff in which we are already drowning: more "data", documents, and artifacts. Figure 1: In the artifact-oriented view of work the artifacts (such as diagrams, documents, letters, reports, etc.) are the focus of management attention. This is because the current paradigm of work focuses almost solely on the artifacts (or products) of work. This artifact-oriented paradigm is slowly giving way to a new "process-oriented" paradigm (see Figure 2). 3 Tools for organizational memory.

Knowledge Transfer. In organizational theory, knowledge transfer is the practical problem of transferring knowledge from one part of the organization to another. Like knowledge management, knowledge transfer seeks to organize, create, capture or distribute knowledge and ensure its availability for future users. It is considered to be more than just a communication problem. If it were merely that, then a memorandum, an e-mail or a meeting would accomplish the knowledge transfer. Knowledge transfer is more complex because (1) knowledge resides in organizational members, tools, tasks, and their subnetworks[1] and (2) much knowledge in organizations is tacit or hard to articulate.[2] The subject has been taken up under the title of knowledge management since the 1990s.

Background[edit] Argote & Ingram (2000) define knowledge transfer as "the process through which one unit (e.g., group, department, or division) is affected by the experience of another"[1] (p. 151). Knowledge transfer in landscape ecology[edit] Knowledge Sharing. Knowledge Sharing is an activity through which knowledge (i.e., information, skills, or expertise) is exchanged among people, friends, families, communities (e.g., Wikipedia), or organizations.[1][2] Knowledge Flow[edit] Although knowledge is commonly treated as an object, Snowden has argued it is more appropriate to teach it as both a flow and a thing.[8] Knowledge as a flow can be related to the concept of tacit knowledge, discovered by Ludwik Hirszfeld[9] which was later further explicated by Nonaka.[10][11] While the difficulty of sharing knowledge is in transferring knowledge from one entity to another,[12][13] it may prove profitable for organizations to acknowledge the difficulties of knowledge transfer and its paradoxicality, adopting new knowledge management strategies accordingly.[8] Explicit Knowledge Sharing[edit] Tacit Knowledge Sharing[edit] Embedded Knowledge Sharing[edit] Importance of Knowledge Sharing in Organizations[edit] Challenges in Knowledge Sharing[edit] See also[edit]

Limits to Information Transfer: The Boundary Problem | Ariadne. Printer-friendly version Send to friend Since the early 1980s the aim of knowledge management researchers and practitioners has been to develop technologies and systems to codify and share explicit knowledge efficiently through electronic means. With the growing appreciation of the importance of tacit knowledge [1], we have a new problem: how to facilitate other forms of systematic organisational learning and knowledge exchange where knowledge cannot be codified. In this article we take a further step by looking at the problem of analysing and managing complex knowledge in organisations that have multiple specialised knowledge communities.

Here the challenge for knowledge management is not only to make knowledge available in repositories for dissemination across the firm. Three Approaches to Knowledge Integration across Boundaries There is a trend towards increasing specialisation both in academia and practice. Table 1: Three approaches to managing knowledge across boundaries Summary Jon E. Knowledge Representation and Reasoning. Knowledge representation and reasoning (KR) is the field of artificial intelligence (AI) devoted to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build.

Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets. Examples of knowledge representation formalisms include semantic nets, Frames, Rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers. Overview[edit] This hypothesis was not always taken as a given by researchers. History[edit] Characteristics[edit] KL-ONE. There is a whole family of KL-ONE-like systems. In KL-ONE descriptions are separated into two basic classes of concepts: primitive and defined. Primitives are domain concepts that are not fully defined. This means that given all the properties of a concept, this is not sufficient to classify it.

They may also be viewed as incomplete definitions. Using the same view, defined concepts are complete definitions. Given the properties of a concept, these are necessary and sufficient conditions to classify the concept. The slot-concept is called roles and the values of the roles are role-fillers. See also[edit] Ontology language References[edit] This article is based on material taken from the Free On-line Dictionary of Computing prior to 1 November 2008 and incorporated under the "relicensing" terms of the GFDL, version 1.3 or later. The Speed of Knowledge | KnowledgeVision. In talking with a business executive the other day, the topic of the best way to communicate with employees came up. This particular business has locations around the US and in Canada, the UK and Australia. One of their real challenges has been communicating their evolving strategy in a consistent way – getting everyone reading from the same playbook.

For most large companies, getting an idea out fast often means sacrificing quality of delivery or impact. You can send a PowerPoint deck with a script, but then you hope someone reads it. You can send video files or a link to something streaming, but sent files clog up your email server, and good quality video takes a while to produce – not the timeliest approach. And audio – podcasts or broadcast voicemails – tend to suffer from lack of visuals and aren’t retained as well as their visual counterpart. So we spent some time talking with him about trying out the KnowledgeVision platform to create a compelling message to worldwide staff.

Sociology of Knowledge. The sociology of knowledge is the study of the relationship between human thought and the social context within which it arises, and of the effects prevailing ideas have on societies. It is not a specialized area of sociology but instead deals with broad fundamental questions about the extent and limits of social influences on individual's lives and the social-cultural basics of our knowledge about the world.[1] Complementary to the sociology of knowledge is the sociology of ignorance[2] including the study of nescience, ignorance, knowledge gaps or non-knowledge as inherent features of knowledge making.[3] [4] [5] The sociology of knowledge was pioneered primarily by the sociologists Émile Durkheim and Marcel Mauss at the end of the 19th and beginning of the 20th centuries. Their works deal directly with how conceptual thought, language, and logic could be influenced by the sociological milieu out of which they arise.

Schools[edit] Émile Durkheim[edit] Karl Mannheim[edit] Robert K. Knowledge Community. A knowledge community is community construct, stemming from the convergence of knowledge management as a field of study and social exchange theory. Formerly known as a discourse community and having evolved from forums and web forums, knowledge communities are now often referred to as a community of practice or virtual community of practice. As with any field of study, there are various points of view on the motivations, organizing principles and subsequent structure of knowledge communities. Perspectives[edit] As a web or virtual construct, knowledge communities can be said to have evolved from bulletin board systems, web forums and online discourse communities through the 80s and 90s.

Stemming from social exchange theory, a well-established perspective is to view knowledge communities as a type of exchange. Knowledge communities can also be viewed as a method by which to do organizational or process innovation. Organizational behavior and structure[edit] Pitfalls[edit] References[edit] Legal Case Management. The terms Legal case management (LCM) or matter management refer to a subset of law practice management and cover a range of approaches and technologies used by law firms and courts to leverage knowledge and methodologies for managing the life cycle of a case or matter more effectively.[1][2] Generally, the terms refer to the sophisticated information management and workflow practices that are tailored to meet the legal field's specific needs and requirements.

As attorneys and law firms compete for clients they are routinely challenged to deliver services at lower costs with greater efficiency, thus firms develop practice-specific processes and utilize contemporary technologies to assist in meeting such challenges. Law practice management processes and technologies include case and matter management, time and billing, litigation support, research, communication and collaboration, data mining and modeling, and data security, storage, and archive accessibility. e-Discovery systems[edit] What is System Engineering? Systems Engineering. Knowledge Base. Knowledge-Based Systems. Inference Engine. Knowledge Engineer. Knowledge Engineering. Knowledge Modeling. Knowledge Ecosystem. Polymorphism (computer science)

Community Knowledge Management. Knowledge Management Software. Knowledge Management Software. ITKM Systems. Kmwiki. Personal Knowledge Management. PKM. PKM - Prof. Paul Dorsey. PKM - Prof. Paul Dorsey--相关文章. Knowledge Extraction. Data Mining. IBM - Knowledge Discovery and Data Mining.

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SECI Model of Knowledge Dimensions. eKC - eKnowledgeCenter. EFQM Excellence Model and Knowledge Management Implications. Framework for Knowledge Management Tools and Projects. Service Knowledge Management System from the Course ITIL Foundations.