Book Description
Ontologies provide a common vocabulary of an area and define - with different levels of formality - the meaning of the terms and the relationships between them. Ontologies may be reused and shared across applications and groups Concepts in the ontology are usually organized in taxonomies and relations between concepts, properties of concepts, and axioms are typically used for representing the knowledge contained in ontologies. With the growth of information available, e.g. on the WWW, they are popularly applied in knowledge management, semantic web, natural language generation, enterprise modelling, knowledge-based systems, ontology-based brokers, e-commerce platforms and interoperability between systems. This book looks at questions such as: * What is an ontology? * What are the uses of ontologies? * What types of ontologies exist? What are the most well-known ones? * How do I select the best ontology for my application? * What are the principles for building an ontology? * What methodologies should I use to build my own ontology? Which techniques are appropriate for each step? * How do software tools support the process of building and using ontologies? * What language can I use to implement ontologies? * How can I integrate ontologies in a given language? The book presents the theoretical foundations of ontological engineering and covers the practical aspects of selecting and applying methodologies, tools and languages for building ontologies. The applications of ontologies are also illustrated with case studies taken from the areas of knowledge management, e-commerce and the semantic web.
Customer Reviews:
how to automatically extract an ontology?.......2006-10-09
The book shows progress in how ontologies are defined from various data sets. The subject is a natural field of artificial intelligence, in attempting to automated this filling of an ontology. Various example ontologies are presented, along with the markup languages like RDF and OWL in which these are expressed. The progress is visible, inasmuch as just a few years ago, these languages were devised. Now we see non-trivial ontology constructions using them. Good.
A large portion of the book describes the acute problem of somehow extracting meaning in a programmatic manner from data. Because the manual making of an ontology simply does not seem to scale, given the realities of gigabyte databases. We see that there is a natural decomposition of the problem into a linguistic step and a conceptual step. The former is tied to a particular human language. The latter is the nut of the problem. Current methods look promising, but are certainly not the last word.
Excellent survey book on Ontology.......2006-03-09
The book is well organized in introducing the subject in a coherent manner and weaving in all important criteria of ontology together. I especially like to read the comparison of different languagees in light of knowlege represenation and knowlege reasoing. The book is great in terms of getting a broad view (survey) and is also great as a reference. In many pages, there is so much information packed in each sentences. Great book.
A good literature review of current developments.......2005-12-15
The word `ontology' is usually associated with philosophical speculation on the reality of things, and if one checks the literature on philosophy one will find a diverse number of opinions on this reality. Engineers and scientists typically view philosophical musings on any topic as being impractical, and indulging oneself in these musings will cause one to lose sight of the topic or problem at hand. Rather than simplify the problem and make it understandable, philosophy tends in most cases to complicate it by endless debate on definitions and the use of sophisticated rhetoric that seems to have no bearing on the problem at hand. The conceptual spaces generated by these debates can become gigantic and therefore unwieldy, thus making the problem appear more complex than it actually is.
In the information age however, ontology has become a word that has taken on enormous practical significance. Business and scientific research are both areas that have increasingly relied on information technology not only to organize information but also to analyze data and make accurate predictions. In addition, financial constraints have forced many businesses to automate most of their internal processes, and this automation has brought about its own unique challenges. This push to automation usually involves being able to differentiate one thing from another, or one collection of data from another, or one concept from another. Thus one needs to think about questions of ontology, and this (very practical) need has brought about the rise of the field of `ontological engineering', which is the topic of this book.
The authors have given a good general overview of the different approaches to the creation of ontologies. There are many of them, some of which seem "natural", while others seem more esoteric. The reader though will obtain an objective discussion of the ontologies that the authors chose to include in the book. Discussions of the ones that are not included can readily be found on the Internet.
Given the plethora of ontologies that have been invented, it would be of interest to the ontological engineer to find common ground between them. The re-use of a particular ontology may be stymied by the different ontological commitments it is adhering to or it's actual content. In order to use it, it must therefore be "re-engineered". The authors discuss this prospect in the book, and define `ontological re-engineering' as the process where a conceptual model of an implemented ontology is transformed into one that is more suitable. The code in which the ontology is written is first reverse engineered, and then the conceptual model is reorganized into the new one. The new conceptual model is then implemented.
Also discussed in the book, and of enormous practical interest, is the automation of the ontology building process. Called `ontology learning' by the authors, they discuss a few of the ways in which this could take place. One of these methods concerns ontology learning using a `corpus of texts', and involves being able to distinguish between the `linguistic' and `conceptual' levels. Knowledge at the linguistic level is described in linguistic terms, while at the conceptual level in terms of concepts and the relations between them. Ontology learning is thus dependent on how the linguistic structures are exemplified in the conceptual level. Relations at the conceptual level for example could be extracted from sequences of words in the text that conform to a certain pattern. Another method comes from data mining and involves the use of association rules to find relations between concepts. The authors discuss two well-known methods for ontology learning from texts. Both of these methods are interesting in that they can apparently learn in contexts or environments that are not domain-specific. Being able to learn over different domains is very important from the standpoint of the artificial intelligence community and these methods are a step in that direction. The processes of `alignment', `merging', and `cooperative construction' of ontologies that are discussed in the book are also of great interest in artificial intelligence, since they too will be of assistance in the attempt to design a machine that can reason over multiple domains.
The ontologies that are actually built are of course not unique. This results in a kind of semantic or cognitive relativism between the environments that might be built on different ontologies, even in the same domain. Merging and alignment both address this relativism, along with other techniques that are discussed in the book. The selection of the actual language that is used to create an ontology is also somewhat arbitrary. The authors devote a fair amount of space in the book to the different languages that have been used to build ontologies. Through an elementary example, they discuss eleven different languages, namely KIF, Ontolingua, LOOM, OCML, Flogic, SHOE, XOL, RDF(S), OIL, DAML+OIL, and OWL. The choice of a language is dictated by what one is seeking in terms of `expressiveness' and what kind of reasoning patterns are to be deployed when using the ontology. The authors point to a tradeoff between the expressive power of the language and the reasoning patterns that are attached to the language. The expressiveness of a language is directly proportional to the complexity of the reasoning patterns that are used.
Ontological engineering as it presently exists is still carried out by a human engineer. To create an ontology every time from scratch would be tedious, and so it is no surprise that tools were invented to make ontology creation more straightforward. Some of these tools are discussed in the book, such as KAON, OilEd, Ontolingua, OntoSaurus, Protege-2000, WebODE, and WebOnto, along with assessments as to their utility. The discussion is helpful for newcomers to ontological engineering who need guidance as to what direction to take. The automation of ontology building would of course be a major advance. To accomplish this however would require that the machine be able to simultaneously and recursively construct the knowledge base and reason over it effectively. This is a formidable challenge indeed.
Good overview for beginners.......2005-04-12
The subject of this book is incredibly relevant to today's world of information management. The chapters are presented in a logical and informative way, though some of the book only skims the surface or barely touches on significant developments, tools, and problems. Overall, I found the text too theoretical, with insufficient ties to messy real-world issues.
Very good.......2005-02-18
There are several chapters that I liked and found very useful. The first chapter on theoretical foundations has been well written. Parsing through the various definitions of Ontology has been an educating experience. The other chapters, especially the ones describing the methodologies and languages are very informative. It may not be exhaustive but for a beginner, these chapters give a good overview.
I was disappointed only when I learnt that the book will not cover Ontology learning tools. The author argues for limiting the scope of the book. I feel the book would have been more valuable had it contained at least an overview of the learning tools!
Book Description
Breakthrough Research on Knowledge Transfer Reveals Five Proven
Methods for Making Knowledge Sharing a Reality--Which are Right for Your Company?
While external knowledge--about customers, about competitors--is critical, it rarely provides a competitive edge for companies because such information is equally available to everyone. But internal "know-how" that is unique to a specific company--how to introduce a new drug into the diabetes market, how to decrease assembly time in an automobile plant--is the stuff of which sustained competitive advantage is made. Nancy Dixon, an expert in the field of organizational learning, calls this knowledge borne of experience "common knowledge," and argues that in order to get beyond talking about knowledge management to actually doing it, companies must first recognize that all knowledge is not created--and therefore can't be shared--equally.
Creating successful knowledge transfer systems, Dixon argues, requires matching the type of knowledge to be shared to the method best suited for transferring it effectively. Based on an in-depth study of several organizations--including Ernst & Young, Bechtel, Ford, Chevron, British Petroleum, Texas Instruments, and the U.S. Army--that are leading the field in successful knowledge transfer,
Common Knowledge reveals groundbreaking insights into how organizational knowledge is created, how it can be effectively shared--and why transfer systems work when they do.
Until now, most organizations have had to rely on costly "trial and error" to find a knowledge transfer system that works for them. Dixon helps managers take the guesswork out of this process by outlining three criteria that must be considered in order to determine how a transfer method will work in a specific situation: the type of knowledge to be transferred, the nature of the task, and who the receiver of that knowledge will be. Drawing from the successful--but very different--practices of the companies in her study and providing compelling illustrative stories based on the experiences of real managers, Dixon distills five distinct categories of knowledge transfer, explains the principles that make each of them work, and helps managers determine which of these systems would be most effective in their own organizations.
Common Knowledge gets to the heart of one of the most difficult questions in knowledge transfer today: What makes a system work effectively in one organization but fail miserably in another? Going beyond "one-size-fits-all" approaches and simple generalities like upper management involvement and cultural issues, this important book will help organizations of every kind construct knowledge transfer systems tailored to their unique forms of "common knowledge"--and in the process create the best kind of competitive advantage there is: the kind that can't be copied.
Customer Reviews:
A very useful taxonomy of knowledge transfer techniques.......2003-01-23
Looking for in-depth case studies of KM in action at large organisations? This book offers a superb collection and analysis of knowledge transfer techniques at companies like Ernst&Young, Bechtel, Ford, Chevron, British Petroleum, Texas Instruments, and the U.S. Army.
The material is divided into 9 chapters, and the writing style is very focused and precise. Useful flowcharts and checklists make the material a must-read for KM professionals and management strategists.
Dixon begins by deconstructing some common myths ý such as ýbuild it and they will come.ý Knowledge transfer which is merely based on accumulating electronic databases will bring about neither appropriate contributions nor adequate retrievals; incentives, discipline, actionable results, alignment with objectives, and face-to-face communication are key requisites.
Going beyond broad generalizations of organizational knowledge management, the book focuses specifically on the issue of knowledge transfer, and identifies five key categories of lesson sharing in large companies: serial transfer, near transfer, far transfer, strategic transfer and expert transfer.
They differ in terms of who the intended knowledge receiver is (same or different from the source), the nature of the task involved (frequency and routine), and the type of knowledge being transferred (tacit/explicit).
One chapter each is devoted to the five kinds of transfer mechanisms, and two chapters tie all the material together in terms of guidelines for building knowledge transfer systems.
In serial transfer, the collective knowledge a team has gained from doing its task in one setting is transferred to the next time that the same team does the task in a different setting. The tasks are frequent, so meetings are held regularly and assessment questions are standardized.
In near transfer of explicit knowledge, the source and recipient teams are different ý but the tasks are quite similar. The tasks are routine; selected goal-oriented information is disseminated electronically, along with supplemental personal interaction; information usage is monitored and assessed.
In far transfer, the tacit knowledge a team gained from doing a non-routine task is made available to other teams doing similar work in another part of the organization. There is a reciprocal exchange of knowledge, and face-to-face meetings as well as movement of experts are involved.
Examples include BPýs Peer Assist (initiated in 1994, to share experience in challenging areas like deciding whether to invest in a new rig; the transfer includes a visit to rig sites by peers), Chevronýs Capital Project Management (with online forums as well as physical movement of project managers to spread learned lessons across the company), and Lockheed Martinýs LM21 Best Practices (to identify and eliminate redundant facilities, capabilities and structures across its 30 subsidiaries; assessments were made of performance and financial performance).
Other examples include Japanýs Dai-Ichi Pharmaceuticals, where researchers are expected to spend 20 minutes a day in ýtalk roomsý where anyone can dialogue with them. ýTacit knowledge can be transferred by moving the people who have the knowledge around. Calling on tacit knowledge is not just a memory task, it is as often an act of creation or invention,ý says Dixon.
Top-level commitment to the process is called for. Some companies like Ernst&Young designate certain knowledgeable people as ýshared resources,ý who spend a chunk of their time sharing their knowledge companywide.
Strategic transfer is called for when the collective knowledge of the organization is needed to accomplish a strategic task that occurs infrequently ý but is critical to the whole organization. The knowledge gathering is conducted during the actual operation; it can be expensive and resource-intensive, and also involves knowledge specialists who collect information, conduct interviews, videotape discussions, interpret the examples, and synthesise knowledge.
A useful methodology here is MITýs ýlearning historyý process, which results in a narrative document describing an event and incorporating quotes from multiple sources and even contradictory perspectives. The process should include subsequent reflective research and validation. These events need not have to be the ýbest,ý but will always have useful learnings.
The resulting documentation from strategic transfer can be disseminated on Intranets, and should have guidelines, checklists, people profiles, contact information, colourful overall narratives, records, and artifacts. Once created by KM specialists, the product is handed over to a community of practice that has the responsibility of keeping it current.
Expert transfer involves the transfer of explicit knowledge from an expert to someone who faces a problem beyond their current scope. Knowledge is pulled from the expert on demand, via threaded electronic forums to which support is dedicated for monitoring, escalation and support.
Examples include Buckman Labýs TechForums (started in 1992, monitored by librarians and sysops, and supported by editorial help in producing weekly summaries of discussions), Tandem Computerýs Second Class Mail (for tech support), Chevronýs Best Practices Resource Map (a yellow pages of employee resources), the World Bankýs internal help line, and Ernst&Youngýs Knowledge Stewards. Online infrastructure is critical here for multinationals, and there can be infrastructure problems in developing countries.
In terms of RoI, Ford reportedly claims that US$34 million were saved in just one year by transferring ideas between Vehicle Operations plants; Texas Instruments saved enough from transferring knowledge between wafer fabrication plants to pay for building a whole new facility.
The books shows how each organization can have multiple ways of transferring knowledge, involving databases, response systems, monitoring, meetings, and dedicated KM staff. Appropriate audits of knowledge assets, knowledge gaps, existing knowledge flows, and critical processes need to be conducted, sometimes with external assistance.
As for branding knowledge transfer initiatives, Dixon observes that they often donýt even mention the word ýknowledgeý ý the emphasis is on words like peering, assistance, team building, and networking.
In sum, this book provides an excellent view of knowledge practices right from the trenches of companies at the cutting edge of KM. The inductive analysis and roadmaps for implementing knowledge transfer are essential reading for knowledge professionals in all manner of large organizations.
>>>>>>>
Madanmohan Rao is the author of "The Asia-Pacific Internet Handbook" and can be reached at madan@inomy.com
Read This Before Foisting KM on Your Org...........2002-02-08
In presenting alternative systems of knowledge sharing, and their strengths and weakenesses for the types, times, and range of knowledge, Dixon's best contribution is to guide the reader from following certain dead-ends, though not necessarily ensuring a success down the right path.
This book, though incredibly well-written in clarity and focus, is not so practical for the working manager faced with creating a "KM Solution" that will stick, as it is for those task forces and executives thinking about KM solutions and wanting to avoid mistakes - oh so common in today's organizations!
So, if you are looking for high-level descriptions of the various systems of knowledge sharing, their strenghts and weakenesses, the cases in the book are lively, thought-provoking, and interesting to follow along.
Cashing in on "Common Knowledge".......2001-11-02
The author focuses on only one type of the many possible types of knowledge that reside in a workplace: the knowledge that employees learn from doing the organization's tasks. She terms this kind of knowledge as "Common Knowledge" to differentiate it from book knowledge or from lists of regulations or data bases of customer information.
The author puts high value to this type of knowledge because it is unique to a specific company. This specificity in turn gives the knowledge gained from experience the potential to provide an organization with a competitive edge. The author points out that although other types of knowledge - such as, customer information and competitor intelligence - must be made widely available; they have less potential to provide a competitive advantage because the same knowledge is equally available to competitors. It takes a certain amount of intention, the author points out, to create common knowledge out of an experience. This involves a willingness to reflect back, a postmortem, on actions and their outcomes before moving forward to another project. This allows a team to build knowledge on what worked well so that the successes are replicated while the failures are avoided.
The author spends less time on organization and storage of information and concentrates her efforts to knowledge transfer. One of the myths the author dispels regarding the organization and storage of information is the myth that if management builds a "warehouse" of knowledge, the worker's that need the information will come and take out what they need. Apparently the notion of knowledge being documented and located in a central place offers a comforting sense of control and manageability. Most organizations therefore build a central electronic database, a perfect fit for the warehouse image but to their dismay, having spent a lot of money to create the database, find that very little in the way of contributions and retrievals occur with much enthusiasm.
Most companies will attempt to "fix" the lack of contributions by offering an incentive system that offers rewards to workers who contribute and retrieve knowledge. Although the incentives work to some extent, the do not deliver the hoped for results. The author contends that the answer is not in better incentives but rather in altering the powerful originating image of a warehouse that places the focus on collecting and storing of knowledge instead of placing focus on reusing it. The reuse of knowledge is the ultimate goal.
The author spends a considerable amount of time on the issue of exchange (leverage or transfer) of knowledge in the workplace. Again two myths are dispelled regarding the exchange of knowledge. One is that technology can replace face-to- face exchanges. Although technology allows workers to share knowledge without having to be in the same place it cannot replace face-to-face interactions. Technology has to be married with face-to-face interaction to create the most effective knowledge transfer systems; one does not replace the other although one can greatly enhance the other.
The author also dispels the myth that one has to create a learning culture first in order to have effective knowledge exchange. She contends that it is really the other way round, that is, if people begin sharing ideas that they see as really important, the sharing itself creates a learning culture. The exchange therefore imparts positively on the learning culture. She contends that people are generally willing to share knowledge in an organization if they are acknowledged and respected for their expertise. If they share their knowledge, then the knowledge is held in common - common knowledge that is shared throughout the organization and gives that organization a competitive edge.
The author notes that regarding the transfer of knowledge, "one size doesn't fit all". Unless the transfer system is appropriate fit for the kind of knowledge and task, it may be ignored and eventually abandoned. What knowledge exchange method is used in a specific situation depends on three criteria:
· Who the intended receiver of the knowledge is in terms of similarity of task and context.
· The nature of the task in terms of how routine and frequent it is.
· The type of knowledge that is being transferred.
Once the criteria above are identified for each situation then the knowledge exchange mechanism is devised. The author discusses five categories of knowledge transfer, each of which requires different design elements to make the transfer work. The five categories are Serial Transfer, Near Transfer, Far Transfer, Strategic Transfer and Expert Transfer.
The author discusses the design of an integrated system for knowledge transfer based on the needs and resources of an organization. She points out that the design of a knowledge transfer system should be based on the thought of knowledge as dynamic and that conduits to enhance its flow should be designed rather than warehouses for its storage.
Useful Intro to KM.......2001-11-01
This is the first and only book I've read about knowledge management, so my perspective is limited. Nonetheless, I found it helpful in organizing my thoughts about processes already in place in my organization that are within the scope of KM (but not formally labeled as such), and in considering how our team might use these systems more effectively. Our organization-wide KM program is still in the planning stages. After reading Common Knowledge, I was able meet with out KM program leader and not sound uninformed.
The author's most important point - that KM solutions cannot take a one-size-fits-all approach - is clearly and convincingly supported. No book is perfect for every reader, however. After a few of the book's case studies, the rest had diminishing returns for me. I also didn't get much value from the author's comments on learning theory, although this might be of interest to true KM aficionados. Overall, I would still recommend the book to managers who are already involved or expect to be involved in implementation of their organization's KM programs.
Common to Public Health, too!.......2001-11-01
Common Knowledge: How Companies Thrive by Sharing What They Know, by Nancy M. Dixon (Harvard Business School Press, 2000), provides valuable insight into the idea of common knowledge, differentiating the types of knowledge transfer, and providing strategies to achieve the types of knowledge transfer described in the book. Her work is largely business focused, the author having looked at major corporations such as Chevron, Ernst and Young, Ford, Bechtel, and British Petroleum. However, she also uses a successful model developed by the U.S. Army. I read the book from a public health perspective, focusing on examining the relevance of each knowledge type and strategies to my own perspective in public health programs. In this paper, I will present the book's perspective, and intertwine the potential application in the public health arena, which was quite abundant in the book.
The author defines common knowledge as the knowledge that employees can learn from doing organizational tasks. It is the know `how' of a company verses the know `what'. It applies to information that is unique to a company or corporate culture. (Page 13)
The author's goals are to 1) broaden the reader's thinking about how a company might share knowledge, not only the `how', but the `why', as well, and 2) to allow readers to determine which system(s) would be most effective in their own settings. Her focus is on teams, not individuals.
The book begins by dispelling three myths about knowledge sharing:
1. "Build the technology and they will come" mentality. A common mistake made is that a knowledge transfer system is put into place and lays largely dormant or improperly used.
2. Technology can replace face to face encounters. She uses experiences from the Ford motor company as her model example here. Several years ago they began sending key staff to overseas Ford plants to exchange ideas, which ended up saving tens of millions of dollars to the corporation. They have a built in mandate that each year a given plant will increase efficiency by 5%, no small task year in and year out!
3. That you must first develop a learning culture. It is believed by many that successful corporations greedily hang on to information to maintain a competitive edge. The author found quite the contrary to be true in the successful corporations she examined, at least from within a complex organization.
Personally, the `knowledge is power' mentality has prevailed at times in our own public health professional environment. When I began in public health the motto of many of my superiors was `keep your cards close to your chest', get as much information as you can without divulging much; however, that thinking has largely changed as public health systems have changed from direct service orientation to linkage to service and collaboration. Also, an anecdotal observation is that a sharing mentality is healthy and that withholding information breeches the trust of the public health and creates divisions within an organizational structure.
The author distinguishes between two important types of knowledge, explicit verses tacit. Explicit knowledge is knowledge that could be directly transferred to the learner in the form of a recipe or manual. If you follow the directions, then you will achieve the same product. Tacit knowledge is the knowledge that a highly trained, or technically complicated, situation occurs. There is a tacit knowledge base in the expert, but at each decision node, there is a complicated array of possibilities, not easily conveyed in a simple manual. Examples of tacit knowledge would be: a cardiologist examining a heart patient. In this scenario there are numerous factors to consider, such as patient history, blood chemistry, vascular and stress tests, genetics, age, race/ethnicity, gender, smoking history, etc. To make the correct decision, the physician must look at many facets of the patient, using his/her accumulated wealth of knowledge about the subject. The idea of tacit knowledge is important in public health in that, where national and state agencies are involved, best practices and experiences, if properly conveyed to a receiving organization, can benefit that organization or jurisdiction. Often, it is tacit knowledge that is needed to best determine what the best fit for an agency is, and what formula or recommendations might work best.
"Tacit knowledge is not only the facts but the relationships among the facts - that is, how people might combine certain facts to deal with a specific situation" (Page 94). Some organizations have begun to designate certain knowledgeable people as "shared resources", with the expectation that a portion of their work time be spent sharing their knowledge company-wide, leaving the other 90 percent for the project.
In chapter 2, the author argues that, in order to create and leverage common knowledge an organization must:
1. Determine effective ways to translate ongoing experiences into knowledge, and
2. Transfer knowledge across time and space.
Many organizations fail to allow for time to debrief a project team or review a recently completed event. If some analysis of the process does not occur, an organization may achieve extraordinary success along the way on a given project and not be able to replicate that knowledge in future projects.
In the author's view, one size does not fit all, (Page 21-22). To determine how a knowledge transfer method will work, one must consider:
1) Who the intended receiver is, in terms of task and context? What is the receiving team's aborptive capacity? In other words, the team receiving the knowledge transfer must have a level of understanding already to `absorb' new knowledge (i.e., you can't learn division until you understand multiplication!). Being able to function as a team increases the absorptive capacity to implement knowledge transfer.
2) The nature of the task, i.e. whether it is routine/non-routine and how frequent the task is.
3) The type of knowledge being transferred - tacit or explicit.
Types of knowledge transfer:
1. Serial Transfer: A team performs a task and then repeats the task in a new context. Examples given were the U.S. Army's After Action Review (or, AAR), that examines what was supposed to happen, what happened, and what accounts for the change. Some private corporations have adopted a similar model.
The receiving team (which is also the source team in this case) does a similar task in a new context. The nature of the task is both frequent and non-routine. It may involve tacit or explicit knowledge.
An example of serial transfer in a public health context might be: A syphilis elimination team engages in a syphilis blitz in Birmingham, then, later in Miami - similar tasks, but different contexts.
Meetings are held regularly and are brief. Everyone is involved in action participation. There are no recriminations. Reports are not forwarded to other levels, though notes are retained for local use. Meetings are facilitated locally.
Some of the barriers to this strategy are that team members won't take the time to meet and discuss. Team members may lack the proper skills to have knowledge producing conversations. Also, staff may disperse prior to the end of the project period. This can be especially true at the local public health level, where staff may be young, underpaid, and trying to advance their careers.
To successfully implement serial transfer, the following should be in place:
q A standardized format of questions
q A team facilitator
q Basic norms of truth telling
q A no recriminations policy
2. Near transfer: Transferring explicit knowledge from a source team to another team doing a similar repeated task in a similar context but in a different location or context. In this context users specify the content and format of the knowledge being transferred.
Knowledge is `pushed', meaning that the information appears automatically, rather than users searching for the knowledge. In the modern context this could be through emails or electronic bulletins. The information is actively disseminated, with brief, not lengthy, explanations. The context of the messages being pushed is very specific. The author points out (page 72) that comprehensive systems usually fail, there's just too much information, so nothing ends up being important. Targeted databases work better.
The goal of Near Transfer is not to share knowledge, but to meet a specific business goal established by management.
Barriers to near transfer are based in people's fears of little-used data-bases, or a frustrated attempt to get teams to use a new or innovative practice or process. Some organizations have cultures that are resistant to outside successes. "If it wasn't invented here we won't use it." Finally, some people are `too busy to share' successful approaches.
Public health example: During the Global Smallpox elimination effort, prior to the electronic age, initial efforts involved attempts to vaccinate all people; however, there wasn't enough vaccine to do this worldwi
Book Description
The large-scale and almost ubiquitous availability of information has become as much of a curse as it is a blessing. The more information is available, the harder it is to locate any particular piece of it. And even when it has been successfully found, it is even harder still to usefully combine it with other information we may already possess. This problem occurs at many different levels, ranging from the overcrowded disks of our own PCs to the mass of unstructured information on the World Wide Web.
It is commonly understood that this problem of information sharing can only be solved by giving computers better access to the semantics of the information. While it has been recognized that ontologies play a crucial role in solving the open problems, most approaches rely on the existence of well-established data structures. To overcome these shortcomings, Stuckenschmidt and van Harmelen describe ontology-based approaches for resolving semantic heterogeneity in weakly structured environments, in particular the World Wide Web. Addressing problems like missing conceptual models, unclear system boundaries, and heterogeneous representations, they design a framework for ontology-based information sharing in weakly structured environments like the Semantic Web.
For researchers and students in areas related to the Semantic Web, the authors provide not only a comprehensive overview of the State of the art, but also present in detail recent research in areas like ontology design for information integration, metadata generation and management, and representation and management of distributed ontologies. For professionals in areas such as e-commerce (e.g., the exchange of product knowledge) and knowledge management (e.g., in large and distributed organizations), the book provides decision support on the use of novel technologies, information about potential problems, and guidelines for the successful application of existing technologies.
Book Description
Based on numerous interviews with top CEOs and other professionals, Managing Interactively helps readers become well-versed communicators in today’s global, technologically focused organizations. Best-selling author Mary Boone examines the techniques and issues that surround clear and effective communication skills in the rapidly changing digital environment and presents provocative new ideas that will help readers address today’s communication challenges. Distilling the experience of top executives into easily applied techniques, each chapter features actual stories from expert communicators who have learned how to successfully adapt their communication strategies to today’s technologies. Managing Interactively is a must-have for anyone facing the communication challenges of today’s volatile business world.
Customer Reviews:
Packed with mind-expanding ideas.......2001-03-21
Speaking as a corporate communication professional, I can honestly say this is the most stimulating business book I've read. The premise is that organization leaders must go beyond simply seeking buy-in from their employees to a more iterative, interactive (and, ultimately, much more inspiring and effective) process of continually reinventing the organization. This argument is supported with great examples and enough detail to be actionable.
Highly recommended........2000-12-29
Mary Boone has authored a wonderful resource for implementing a knowledge-sharing culture in the Enterprise. Things to pay special attention to in the book include the ten key competencies for mastering new methods of communication and management, her insightful analysis of trends and obstactles affecting corporate communication, and the way she uses interviews with CEOs and executives to show you how others have implemented effective collaborative strategies.
On the lighter side of things, read her story about "George" in the "Get Over Yourself" chapter. She uses this story to point out how personality differences can be a show stopper to implementing innovation and promoting creativity. Furthermore, she explains how collaborative technologies can help bypass some of these differences.
Book Description
The field of knowledge management focuses on how organizations can most effectively store, manage, retrieve, and enlarge their intellectual properties. The repository view of knowledge management emphasizes the gathering, providing, and filtering of explicit knowledge. The information in a repository has the advantage of being easily transferable and reusable. But it is not easy to use decontextualized information, and users often need access to human experts.
This book describes a more recent approach to knowledge management, which the authors call "expertise sharing." Expertise sharing emphasizes the human aspects--cognitive, social, cultural, and organizational--of knowledge management, in addition to information storage and retrieval. Rather than focusing on the management level of an organization, expertise sharing focuses on the self-organized activities of the organization’s members. The book addresses the concerns of both researchers and practitioners, describing current literature and research as well as offering information on implementing systems. It consists of three parts: an introduction to knowledge sharing in large organizations; empirical studies of expertise sharing in different types of settings; and detailed descriptions of computer systems that can route queries, assemble people and work, and augment naturally occurring social networks within organizations.
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Knowledge Sharing in Practice (Information Science and Knowledge Management)
M.H. Huysman , and
D.H. de Wit
Manufacturer: Springer
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Binding: Hardcover
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ASIN: 1402005849 |
Book Description
In this volume organizational learning theory is used to analyse various practices of managing and facilitating knowledge sharing within companies. Experiences with three types of knowledge sharing, namely knowledge acquisition, knowledge reuse, and knowledge creation, at ten large companies are discussed and analyzed. This critical analysis leads to the identification of traps and obstacles when managing knowledge sharing, when supporting knowledge sharing with IT tools, and when organizations try to learn from knowledge sharing practices. The identification of these risks is followed by a discussion of how organizations can avoid them.
This work will be of interest to researchers and practitioners working in organization science and business administration. Also, consultants and organizations at large will find the book useful as it will provide them with insights into how other organizations manage and facilitate knowledge sharing and how potential failures can be prevented.
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It is widely acknowledged that businesses today must harness the Net to effectively utilize the myriad details they glean from--and then pass around to--their various stakeholders. But how best to do that? e-Business Intelligence, by the head of a global company that helps others develop such efforts, lays out a variety of interrelated methodologies already in use by pioneering corporations around the world. In doing so, author Bernard Liautaud explains how to move from data (the extensive raw stats to which most contemporary firms are privy) to information (the proper context in which they must be applied) to intelligence (the collective knowledge from which appropriate actions are initiated). Liautaud shows how companies like Eli Lilly, MasterCard, and British Airways have created electronic relationships among employees, suppliers, consumers, and business partners to boost marketing, customer service, quality control, purchasing, and other activities. He explains how internal "information democracies" allow them to instantaneously distribute pertinent details throughout their organizations, while external "information embassies" facilitate the rapid transfer of pertinent facts to outside constituencies. To help readers develop their own individualized strategies, he presents specifics on gathering "customer intelligence," sharing product information, optimizing supply chains, and performing other critical tasks. --Howard Rothman
Book Description
Internationally celebrated ebusiness innovator, Bernard Liautaud, explains why the key to ebusiness success is knowing how to transform the vast reservoir of raw data found in every company into a corporate intelligence gold mine.
This book focuses on the three main areas of ebusiness intelligence—intranets, extranets, and business-to-business ecommerce. He describes cutting-edge strategies for accessing, analyzing, and sharing corporate data both internally and externally with customers, partners, and suppliers. With the help of case studies from Lucent, Dow Chemical, Disney, Go Network, and other ebusiness giants, Liautaud explains the what, why, and how of ebusiness intelligence in the new information economy.
Bernard Liautaud (Palo Alto, CA) is CEO of Business Objects, the world's leading provider of ebusiness solutions, and, according to Intelligent Enterprise magazine, one of the "12 Most Influential Companies in the Information Technology Industry." In 1996, five years after founding Business Objects, Liataud was named one of BusinessWeek's "Hottest Entrepreneurs of the Year."
Customer Reviews:
very good.......2006-02-03
Great for someone who is looking to expand his knowledge of what is BI and how to use it to improve his performance results.
Buy it, worth the money!
Exactly to the point.......2005-03-12
This book goes exactly to the point that hurts most of the companies even in this days of year 2005. It will take some time to define the standards in this BI industry but definitely this book marks the beginning of it. Other more detailed more sophisticated books might be written by others but the most difficult is to write the first one. Others inspired by this book will probably write new ones.
Not enough details to be useful.......2003-08-19
I found this book to be very weak in details and concepts. It's easy to say that companies need business intelligence and throw around some very vague and general facts and examples. And that's what this book does. The case studies offer no details at all. If you've never heard of e-business or intelligence (basically if you've been living in a cave) then this book will introduce the topic at a high level. But if you're looking for more information you'd better look some place else. I know the author is the founder of Business Objects, but I just expected more from this book and was very disappointed.
No business intelligence, just business promotion.......2002-11-27
While doing periodical research on the business intelligence subject, I found this book as a new acquisition at the university library; sorry, but it is a long white paper on the advantages and why to use a software tool for doing business intelligence, never minding about any data/facts that may be found out of the bits and bytes world: Informal sources? External data? Competitor intelligence? Who cares, if you want a 360° view of your customer, don't need more than a computer and some software--at the end, culture, attitude and pure business sense seem like a waste of time. Suddenly, I discovered why this bothered me: The autor is one of Business Objects' top executives! Now, it all made sense: It is like other books written by people who need to sell a product (and Business Objects is a good seller indeed) so writting down their way of seeing the world gets them a guruesque position in front of their customers and prospects. If you need to really learn about business intelligence, don't bother reading it: you can find lots of free white papers that cover the same subject in the BI software vendors web sites. Trying to understand business intellingence as something that needs nothing more than a software tool, leaving behind all the intelectual and analytical work to do, is equivalent to define mathematics as the use of a scientific calculator.
Should be read by all managers!.......2002-08-26
This book was written for managers in mind. This book does not cover technical details of data warehouses or data mining. Given its scope this book accomplishes its task efficiently, with no real wasted anecdotes and personal opinions. The author a well-known expert on business objects really displays his ability to convey the information accurately and illustrates his points well. This will aid any manager get up to speed on the missing information sources that can occur in any business and apply them to their own business. Overall, this book accomplishes what it intends to do and that is to inform the reader on the various methods a business can utilize information to gain efficiency and a competitive advantage in the marketplace.
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Conceptual Structures: Common Semantics for Sharing Knowledge: 13th International Conference on Conceptual Structures, ICCS 2005, Kassel, Germany, July ... / Lecture Notes in Artificial Intelligence)
Manufacturer: Springer
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Binding: Paperback
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ASIN: 3540277838 |
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This book constitutes the refereed proceedings of the 13th International Conference on Conceptual Structures, ICCS 2005, held in Kassel, Germany, in July 2005. The 23 revised full papers presented together with 9 invited papers were carefully reviewed and selected from 66 submissions. The papers are organized in topical sections on theoretical foundations, knowledge engineering and tools, and knowledge acquisition and ontologies.
Book Description
Get wise to the knowledge within your organization.... Within every company, a small group of people exist who know how to get things done: how to solve big problems that stump others, navigate obstacles, and anticipate emerging opportunities with amazing speed. But most companies don't make the best use of their wisest people...or even know who they are. The Wisdom Network introduces readers to an eight-step process for discovering and realizing the power of the untapped knowledge that exists within their organization. The book shows how to:
* establish an environment that encourages wisdom sharing and expansion of roles * identify "magnet" topics vital to the company and support ad hoc teams of experts that form around them * create unconventional measures to track the progress of the wisdom network
Employees who continuously prove their worth can be found at all levels of the organization. Here's how to reap the true value of their wisdom.
Book Description
This digital document is a journal article from Information & Management, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
The Internet provides an opportunity for knowledge sharing among people with similar interests (i.e., buddies). Emails, mailing lists, chat rooms, electronic bulletin boards, newsgroups are ways for identifying buddies. However, manual ways of finding a buddy are time consuming and not generally effective. Collaborative filtering technologies can provide useful information to users based on others' interests, and software agent technology is a promising tool for finding buddies. Software agents are autonomous and can represent users' preferences and perform tasks with built-in learning and reasoning capabilities. They can also communicate with one another to exchange information. Here, we define an agent-based buddy-finding methodology. Agents are created to represent users and exchange sample information with possible buddies while assessing the information exchanged. Thus, we present a methodology for developing an agent that identifies a set of buddy-agents using a built-in fuzzy reasoning mechanism to assess the buddy membership of peer agents. Using this, the agents cultivate a dynamic acquaintance list of their peer agents. The methodology was empirically tested in a context involving sharing musical-knowledge. We show that the buddies found by agents are as good as those found manually. lly.
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