This paper presents extensions that have been programmed by the Department Social Learning (DSL) at Graz University of Technology (TU Graz) for a blogosphere used at TU Graz called TU Graz LearnLand (TUGLL) on base of the open source software ELGG. These extensions are useful upgrades to the system following the demands of the pedagogical strategy of the TU Graz. A description of the extensions and didactical considerations are discussed.
Unforeseen Experiences from a Balanced Scorecard Project in the Healthcare Sector
In the context of the Balanced Scorecard development in the Upper Austrian Gesundheits- und Spitals AG (gespag) the methodology of strategy maps was applied in order to build a base for the definition of relevant areas of strategic measures. When applying the methodology it turned out that it is very supportive also from the knowledge management perspective (especially 2nd Generation KM), e.g. for the explication of knowledge, cognitive mapping, the creation of a common-mindset (organisational learning), the storage of information and individual learning about strategy and systemic thinking. Furthermore, it allows organisational knowledge integration meaning that people can integrate both the explicated knowledge in their system or their work, and the appropriate “sense” of the further information provided. The intention of the article is to show that methods of strategic management, and possibly from many other fields, can also be very beneficial in a knowledge management context.
Thematic portals are sites where subject matter experts select and organize information and, consequently, they can be described as top-bottom structures. While challenging this schema, implementing social information retrieval systems and social network representation features can improve user experience and the dissemination impact of the portal. We analyse the characteristics of social software and review examples of utilisation of these technologies that can be applied in an educational technology thematic portal.
Recently, the information community has seen the emergence of user-centric media applications, which are characterized by the central position given to the user. To fulfill the user-centric promise, it is necessary to understand and model the actions of the users of the system. This position paper presents a methodology for modeling the behavior of multimedia database users. To this end, we propose to analyze the query logs to derive the classes of behaviors of a user. The presented method bases on the characteristics of user queries and on taxonomies. The behaviors are established using a query classification algorithm.
Finding expertise is an important task required in all organisations and institutions. In looking for expertise, one typically relies on the compilation of information from multiple sources such as organisational directories and social networks. This approach has been applied to enhance the Journal of Universal Computer Science to enable it to become a still more valuable scholarly resource. This paper describes a multi-faceted representation of expertise, by consolidating human specified expert profile with systemic assessment of expertise. The multifaceted approach is an important in the consolidation of information from multiple sources, in an effort to expand on the characterisation of expertise. The strength of this approach is drawn from the incorporation of intangible metrics for expertise assessment. This paper has revealed interesting directions for the automatic discovery of expertise in scholarly communities.
This paper proposes a conceptual definition that can used as a starting point to contextualize knowledge initiatives in international organizations and other types of non-profit organizations interested in knowledge management.
Organizational leaders, knowledge managers and consultants involved in creating and implementing knowledge management initiatives aimed at process improvements in international organizations context could benefit from the reflections and learning insights from this paper.
This paper does not address efficiency matters from the political or governing sphere, nor does it propose specific programmatic changes to work of international organizations; rather it presents a pragmatic “bottom-up” approach, based on case studies and interviews conducted at eight different international organizations, including the European Union (EU), the International Atomic Energy Agency (IAEA), the International Maritime Organization (IMO), the OPEC Fund for International Development (OFID), the Organization of the Petroleum Exporting Countries (OPEC), the Organization for Security and Co-operation in Europe (OSCE), the United Nations Industrial Development Organization (UNIDO) and the United Nations Office on Drugs and Crime (UNODC) and were classified according to their functional orientation. Over 40 interviews have been conducted, with organizational leaders, knowledge managers, IT managers and human resources managers.
The grounded theory methodology as described by Strauss and Corbin [Strauss and Corbin, 1990, Strauss and Corbin, 1994], using interviews and document studies for data collection, combined with findings from literature, helped identify processes involved in managing knowledge in international organizations.
The quality of the current tagging services can be greatly improved if the service is able to cluster tags by their meaning. Tag clouds clustered by higher level topics enable the users to explore their tag space, which is especially needed when tag clouds become large. We demonstrate TagCluster – a tool for automated tag clustering that harnesses knowledge from Wikipedia about semantic relatedness between tags and names of categories to achieve smart clustering. Our approach shows much better quality of clusters compared to the existing techniques that rely on tag co-occurrence analysis in the tagging service.
Social media sharing sites such as Flickr or YouTube have become immensely popular. Besides sharing actual content, users also share annotations describing or classifying the contents they publish. Although tagging is easy, annotation still is a laborious task that can be made easier by suggesting meaningful additional tags to the user automatically. In this position paper we propose a system architecture and process for supporting annotation by tag suggestion to increase the quality and quantity of social annotations. The goal is not to tag previously untagged images in a completely automatic way, but instead to extend the amount and completeness of annotations by supporting the user in the process of adding further tags.
In this position paper we present a vision of how the stories that people tell in Internet weblogs can be used directly for automated commonsense reasoning, specifically to support the core envisionment functions of event prediction, explanation, and imagination.
In this contribution Wikis are interpreted as social information spaces. These information spaces can be decomposed in different networks. Here, one network is introduced – the collaboration network. This network type exemplifies how dynamics in social information spaces can be analyzed. For this, different approaches of visualizing networks are explained. The chosen approach is applied in an descriptive study. The open community project Wikiversity is examined to introduce one possible analysis in SONIVIS:Tool – an open source ntwork mining software.
A mining method for egocentric and polycentric queries in multi-dimensional networks is proposed. The method allows fast search for objects in sufficient proximity of other object(s) where the proximity is defined in terms of multiple relationships between objects. The method uses spreading activation technique. Other potential uses of spreading activation technique are also outlined and, in particular, include applications to collaborative filtering (community detection based on tag recommendations, expertise location, etc). Moreover, the spreading activation technique is combined with so-called ambient navigation. The advantages of such approach are high performance and high scalability in terms of size of multidimensional network. The proposed method is very practical and is implemented in IBM LanguageWare software products.
BREIN is an FP6 EC-Project dealing with the development of an intelligent grid infrastructure. A key knowledge management challenge to be addressed within the project is the distribution of the results from the project to the software development community, in order to foster the usage of the BREIN middleware. Therefore this project introduces the BREIN Roadmap. The Roadmap is realized applying the knowledge management approach PROMOTE that enables the knowledge transformation and distribution.
Despite the growing importance of knowledge work in today’s organizations, its support by means of ICT tools is still rather limited. Recent trends in semantic technologies provide novel approaches for an effective solution to these challenges in terms of semanticbased task management. However, task management involves the complex interplay of information and work activities. Thus a semantic task management framework is needed which supports an adaptable semantic foundation, to meet the challenges of knowledge work, via a set of task services on the desktop. To this end, we propose the Nepomuk Semantic Task Management Framework (STMF) as platform for a task-oriented ecosystem for desktop applications.
Many enterprises loose work time because they lack of global search solutions or their solutions are not able to satisfy the needs in a reasonable time. This results in costs for lost work time as well as increased response time. We present a novel approach to federated search engines that use case based reasoning to rerank results according to the searchers needs and therefore leads to a higher quality of search results and faster information retrieval.
The knowledge maturing model views learning activities as embedded into, interwoven with, and even indistinguishable from everyday work processes. Learning is understood as an inherently social and collaborative activity. The Knowledge Maturing Process Model structures this process into five phases: expressing ideas, distributing in communities, formalizing, ad-hoc learning and standardization. It is applicable not only for content but also to process knowledge and semantics. In the MATURE IP two toolsets will be develop that support the maturing process: a personal learning environment and an organisation learning environment integrating the levels of individuals, communities and organisation. The development is guided by the SER theory of seeding, evolutionary growth and reseeding and is based on generally applicable maturing services.
One of the most popular and trend-setting Internet applications is People Search on the World Wide Web. In its most general form, information extraction for persons from unstructured data is extremely challenging, and, we are pretty far away from satisfying solutions. However, current retrieval technology is able to cope with restricted variants of the problem, and this paper deals with such a variant, the so-called multi document person resolution. Given is a set of Web documents, and the task is to state for each document pair whether the two documents are talking about the same person or not.
For this problem Spock Inc., Silicon Valley, launched in 2007 a competition offering a grand prize of $50 000. Task was the person-specific classification of 100 000 Web pages within 4 hours on a standard PC, striving for a maximum F-Measure. The paper in hand describes the challenge and introduces the technology of the winning team from the Bauhaus University Weimar [see 1].
When studying heritage artefacts, and trying to represent what we know of them, it is important to portray not only key moments in their evolution, but also processes of transformation. In this contribution, we introduce a methodological framework of description of architectural changes, and investigate diagrammatic representations as means to visualize the above mentioned framework. We introduce two types of diagrams (diachrograms that distribute along a time axis transitions and states, variograms that detail the nature of the changes) that should help better understanding, how changes over time affect architecture. The paper also underlines key aspects of data in “historical sciences”: uncertainties, incompleteness, long ranges of time, unevenly distributed physical and temporal stratifications.
Companies are faced with managing as well as integrating large collections of distributed data today. Here, the challenging task is not to store these volumes of structured and interlinked data but to understand and analyze its explicit or implicit relationships. However, up to date there is virtually no support in navigating, visualizing or even analyzing structured data sets of this size appropriately. This paper describes novel rendering techniques enabling a new level of visual analytics combined with interactive exploration principles. The underlying visualization rationale is driven by the principle of providing detail information with respect to qualitative as well as quantitative aspects on user demand while offering an overview at any time. By means of our prototypical implementation and a real-world data set we show how to answer several data specific tasks by interactive visual exploration.
In the economic and financial analysis domain a quick access to the right information plays a major role. Using current systems, the search for and presentation of data is very cumbersome. The data, mostly in form of time-series, is stored in various databases. In order to retrieve the searched data, the analysts need to know where to search and sometimes even the structure of the database and its coding. Then it is required to export the data, process the data and create a chart to view the data. This might take time from tens of minutes to hours.
In our work we present a first prototype of an integrated search engine that takes as input a natural language query and offers graphic and text output depending on the user task. The system automatically identifies the time-series answers, types of graphical data presentation and shows the results in a web browser and in Excel. The knowledge-based expert system uses domain ontologies for extraction of economic terms in the search queries and specially built data type taxonomy with user task and chart type ontologies for identification of graphic output.
An increasing amount of valuable information is stored in RDF. In order to let humans access this information, providing an appropriate visualization of RDF data is an important challenge. In this paper, we present a new approach, combining list and a graph visualization to counterbalance the respective disadvantages of both representation paradigms to better handle the complexity of both the size and the
structure of RDF data.
In recent years the visualization of knowledge has been gaining wider attention: visualization is said to enhance human capabilities for knowledge intense activities such as decision making and strategic thinking. However, this is a recent field and still widely unexplored. Thus far, the advantages of knowledge visualization have been investigated mainly through anecdotal evidence and qualitative studies. In this paper, we propose an experimental approach to further comprehend the role of visualization in fostering knowledge sharing. We plan to compare the elicitation and evaluation processes of groups who are provided (1) with an optimal visual support, (2) with a sub-optimal visual support, and (3) without any visualization. The goal of our research is to apply the experimental approach – widely used in studying GSS (Group Support System) but seldom used in knowledge management – to shed light on the role of visualization for knowledge-intensive tasks in groups. We report first preliminary results of an experiment with 56 MBA students and also outline the limitations of our approach.
The importance of comprehensive annotations for learning resources is widely recognized. However, it is often unclear how these annotations should be created. A promising solution might be that learners annotate learning resources during execution of learning processes. This paper examines tagging as a learner-driven approach that can be used to get annotations on a collaborative level. The characteristics of learner-generated annotations in learning scenarios and the applicability of these annotations to describe learning resources are investigated. As empirical grounding, the results of three independent experiments are presented in order to inform decisions concerning the establishment of stitutionalized settings deploying tagging approaches.
The stories told among members of an organization are an effective instrument for knowledge socialization, the sharing of experiences through social mechanisms. However, the utility of stories for organizational learning is limited due to the difficulties in acquiring stories that are relevant to the practices of an organization, identifying the learning goals that these stories serve, and delivering these stories to the right people and the right time in a manner that best facilitates learning. In this paper we outline a vision for story-based organizational learning in the future, and describe three areas where intelligent technologies can be applied to automate story management practices in support of organizational learning. First, we describe automated story capture technologies that identify narratives of people’s experiences within the context of a larger discourse. Second, we describe automated retrieval technologies that identify stories that are relevant to specific educational needs. Third, we describe how stories can be transformed into effective story-based learning environments with minimal development costs.
In this paper an approach is presented how self-regulated learning can be supported and stimulated by visualising knowledge and competence structures in order to provide visual guidance in the learning process. In the field of adaptive systems and related research techniques of intelligent guidance have been developed, which, however, may have the disadvantage of limiting the learner. On the other hand, self-regulated learning gives greater control and responsibility to the learner, however, especially weak learner may have difficulties without provision of guidance. The presented approach combines both offering guidance and granting control over the own learning process. A set of learning tools have been developed which implement and demonstrate the proposed approach. Since knowledge structuring and knowledge visualisation are well established in the field of knowledge management, this approach can be exploited to bridge the research fields of e-learning and knowledge
management.
Complex products and services require both the sophisticated knowledge of individuals on the one hand and collective collaboration between various disciplines and teams on the other. Work-related individual and organizational learning processes in organizations appear to provide the foundations for such individual and organizational knowledge and capabilities. These interconnected learning processes would also seem to be situated in both a social and a physical environment. This paper proposes a methodology for managing situated individual and organizational learning. Empirical results from a questionnaire and two test bed organizations are presented and conclusions drawn from the assessment results on recommended measures for the use of e-learning.
In this paper we analyze the meanings and relations of frequently used terms in knowledge management (KM). We start with an overview of the terms data, information, and knowledge, which are mostly seen to be in a hierarchical relation with either knowledge or data on top of the hierarchy. Afterwards, we present the concepts that underlie tacit knowledge, implicit knowledge, and explicit knowledge. Since the meaning of all of these terms varies depending on the author, we give working definitions of the terms and integrate them in a coherent framework, which clarifies and visualizes the relations between data, information, and
different types of knowledge. The framework allows researchers to build on a clear terminology concerning frequently used terms in KM, and helps readers of KM literature to gain a better understanding of their meanings and relations.
Determining fields of excellence in the know-how of knowledge intensive companies is often a crucial decisional process, aimed e.g., at identifying the competence to be strengthened or to invest on in a long term strategy. In this paper we propose a semantic-based approach for automatic extraction of such a specializing knowledge, usually called Core Competence in knowledge management literature. The proposed approach exploits Description Logics as formalism for the representation of knowledge sources and implements novel reasoning services, in particular informative common subsumers specifically devised for Core Competence evaluation.
Several data quality management (DQM) tasks like duplicate detection or consistency checking depend on domain specific knowledge. Many DQM approaches have potential for bringing together domain knowledge and DQM metadata. We provide an approach which uses this knowledge modeled in ontologies instead of aquiring that knowledge by cost-intensive interviews with domain-experts. These ontologies can directly be annotated with DQM specific metadata. With our approach a synergy effect can be achieved when modeling a domain ontology, e.g. for defining a shared vocabulary for improved interoperability, and performing DQM. We present three DQM applications which directly use knowledge provided by domain ontologies. These applications use the ontology structure itself to provide correction suggestions for invalid data, identify duplicates, and to store data quality annotations at schema and instance level.
Despite the obvious business value of visualizing similarities between elements of evolving information spaces and mapping these similarities e.g. onto geospatial reference systems, analysts are often more interested in how the semantic orientation (sentiment) towards an organization, a product or a particular technology is changing over time. Unfortunately, popular methods that process unstructured textual material to detect semantic orientation automatically based on tagged dictionaries [Scharl et al. 2003] are not capable of fulfilling this task, even when coupled with part-of-speech tagging, a standard component of most text processing toolkits thatdistinguishes grammatical categories such as article (AT), noun (NN), verb (VB), and adverb (RB). Small corpus size, ambiguity and subtle incremental change of tonal expressions between different versions of a document complicate the detection of semantic orientation and often prevent promising algorithms from being incorporated into commercial applications. Parsing grammatical structures, by contrast, outperforms dictionary-based approaches in terms of reliability, but usually suffers from poor scalability due to their computational complexity. This paper addresses this predicament by presenting an alternative approach based on automatically building Tagged Linguistic Unit (TLU) databases to overcome the restrictions of dictionaries with a limited set of tagged tokens.
2D barcodes are capable of storing different kind of data. A significant number of new mobile phones come with a built-in camera. These technologies together with the fact that mobile phones are next to the owner most of the time are the foundation of a variety of interesting applications. In Japan more than 75% of all mobile phones do have already a preinstalled barcode reader, that allows the user to decode the incorporated information of a barcode. This procedure can be used to improve the user experience while simplifying the input of data into the mobile device. These 2D barcodes can be used to exchange information
between mobile phones and to connect to the mobile web. These days the Western World is gaining interest in this technology. In this paper the most important applications are introduced. The relevance to print media and the advertising industry is shown.
In today’s information environments, tagging is widely used to provide informationabout arbitrary types of digital resources. This information is created by end users with different motivations and for different kinds of purposes. When aiming to support users in the tagging process, these differences play an important role. This paper discusses several approaches to generate tag recommendations, and a prototypical recommender system for the social resource sharing platform ALOE will be presented.
This interactive system allows users to control the generation of the recommendations by selecting the sources to be used as well as their impact. The component was introduced at DFKI, and a first evaluation showed that the recommender component was considered as helpful by a majority of users.
Story-telling has been a means of bequeathing knowledge since aeons. Whereas the idea of the story-telling remains unaltered, the world around undertakes continuous changes. New media, new technologies and devices, new ways of communication define a new format of the story-telling. This paper proposes a new non-linear version of mobile story-telling in the emerging ubiquity of knowledge sharing. To support our concept we provide a description of multimedia services based on the MPEG-7 metadata standard used for our non-linear mobile story-telling environment.
Our goal is increasing the users’ value and experience and decreasing the implementation time for web portals. To achieve this goal we adopt a subject-centric perspective on information architecture. The fundament of this approach is that portals should be driven by subject-centric models of the portals’ domains. Out of these domain models, the interaction and interface design of the portals is self-evident. Amongst others, the international industry standard Topic Maps is a portal technology and an implementation of the subjectcentric modelling paradigm. With ActiveTM we introduce a technology, which implements a Model-driven approach to automatically create domain-customised, subject-centric portal engines, based on Topic Maps. ActiveTM has proved as technique for reducing the implementation cost of portals enormously and the implied subject-centricness increases the users’ value and experience significantly.
A user-centric architecture of infotainment content adaptation to the context is presented. The architecture uses component technologies in term of business logic and functionalities offered by social web (OpenID, FOAF) and semantic descriptions of MPEG-7 and MPEG-21. Technological alternatives are discussed and adapted to the specificity of vehicle applications in terms of scalability and platform mobility. The requirements of the architecture are motivated by the presentation of a scenario.
The Web 2.0 philosophy has brought new ways of using the web as a content repository and a sharing platform. Non-computer skilled people can now publish their own text, images, videos and/or sounds and take part in communities created around topics they like. It has also brought an opportunity to propose resources to a potentially huge audience. Indeed, a promotional video posted on YouTube can be watched by millions of users. That is why we wanted to know if it was possible to take advantage of this possibility to recruit testers for our music learning tool: our development is user centred, so it is important for us to have it evaluated by lots of testers. Until now, they were recruited in a geographically limited area, i.e Réunion Island. Therefore, we have set up an experiment called “E-guitar Sonar Edition” to gather information about this recruiting opportunity. The idea is thus to design a free downloadable version of our system (originally, it was a DVD), put it on a dedicated web site and have it promoted thanks to video sequences posted on YouTube and Dailymotion, the two majors video Web 2.0 sharing sites, the most appropriate services. This article presents the conditions and the process used. It also deals with the assessment part, the way we gather feedback and finally shows the firsts results. The experiment itself has no limit in time, so it is still currently running.
This paper presents findings from the development process of a general innovation framework for an ongoing Nordic R&D project on e-business and media. It focuses on the current state of the Danish news media sector and the conclusions we can draw from the “Web 2.0 activity” of the Danish newspapers. The paper concludes that the Web 2.0 offers the opportunity for fundamental re-thinking of the business models of the news media sector and for developing a new framework for business modelling for this sector.
The need for Knowledge Management (KM) in Human Services is growing. New “Social Software”-solutions which came along with the so-called “Web 2.0” enable advanced possibilities of implementing KM-strategies in smaller agencies in the domain of Social Work. In the field of of human service-oriented knowledge sharing one case out of three projects showing the use of a wiki will be presented. The project deal with the introduction of a wiki in the area of Case Management in a job center.
Web 2.0 platforms such as media sharing and social network sites (SNS) concern people in everyday life to a great extent. People are enabled to reach out to various media and up to now, it is nearly impossible to use digital identities ex ante or to recreate users’ identities ex post across different platforms. In this paper, we explore important methodologies in Web 2.0 such as cross-media analysis and social pattern based analysis based on a survey in this area, aiming at cross-platform information diffusion across social network sites. Open issues are discussed to explore the challenges and solutions in this new research area.
Wikis have their seeds in the easy collaborative editing and maintenance of web pages. This was picked up by tremendously successful public projects such as the online encyclopedia Wikipedia. Creating, modifying and maintaining of wiki articles implies social structures and dependencies between wiki authors and wiki articles themselves. The general challenge of this work is to consider these structures as dynamic evolving networks and to point out prominent behaviors in large wiki-based networks. We present an environment capable of handling data management, measurement and visualization issues for the dynamic network analysis of publicly available wiki data.
Today Online Social Networks (OSN) are very popular Web sites which show remarkable user growth and attention on the Internet. One reason of the extraordinary success of these social software sites are the enhanced Web 2.0 technologies and concepts, but they do not really explain why a OSN in particular produce explosive growth while another similar Web site is drying out. We belief that these socio-technical mass phenomena can be better understood by introducing self-organization theory (SOT) and crowd behavior. These concepts can explain why spontaneous collective- and herd behaviors may emerge and how the development of these processes could look like. However OSN should not only grow fast, they also want to stay sustainable and get profitable. Hence an important question of these potential “overshoot and collapse” Web sites on the Internet is how to get it stabilized and turned into a long lasting and successful service. Therefore we present some considerations about growth and sustainability in the dynamic and competitive online world.
Although collaboration is widely accepted as the most efficient method for creating value some important barriers of knowledge sharing arise leading to the creation of noncollaborative environments. Especially in developing countries, universities have to face new challenges that rise from shifts in the knowledge production paradigms and from frequent changes in policies. Considering these particularities, we believe that some measures have to be taken to ensure a leap to knowledge sharing, a leap over usual knowledge sharing barriers that arise on traditional approaches to knowledge management implementations.
In this paper we propose a classification and systematic description structure based on the pattern paradigm for interaction scripts in Second Life that aim at facilitating knowledge sharing and knowledge integration in groups. We present eight examples of such interactions, a description structure to formalize them, and classify them into four classes according to their design scope and added value. Based on this classification we distinguish among sophisticated 3D collaboration patterns, seamless patterns, decorative patterns, and pseudo patterns.
This paper introduces the LIR-Schema, a framework to model knowledge flows within a company based on model-theory. Competence management is integrated in this framework as a tool for modelling the contexts of sender and receiver of expertise. The main target of this framework is to reduce the knowledge gap between experts and laymen within the company.
Providing context-aware personalized desktop assistance that is related to the work task of the knowledge worker is a recent research topic. Our approach focuses on task detection by work context observation. A sum of steps towards this goal are addressed by our work, including (1) accessing the desktop computers event stream of user interaction and system status, (2) context reasoning and prediction of the user’s working task and (3) recommending relevant resources based on the predicted work goal. Here, we present an algorithmic approach for automated context aggregation by using mapping functions. This instance of context inference combines lower-level context features to new aggregated features which represent a higher-level context. While related work uses manually defined domain-specific rules for combining features, we automate this approach and in addition show that by means of that the prediction accuracy of the user’s work task increases significantly.
The more information a knowledge worker has to handle, the more (informal) learning is needed right at the workplace. This paper describes an algorithm that enables users to explore their current workflow, jump and navigate through their own tasks (even future ones), for informal learning or help purposes. This is done by overlaying the real workflow with a cloned one, providing an interface to access additional information, like prerequisites, associated documents or expert contacts. In particular, we developed KAJAL, which is a Petri net formalism to cope with the question of determining the states after a jump to a future task was triggered during the user’s navigation.
This contribution promotes the application of an adaptive collaborative management (ACM) approach for social learning in the context of Nepal’s community forestry program. We highlight the principles of the ACM process, the problems, potentials and limitations of the approach especially to demonstrate social and collaborative learning for sustainable community forest management. Researchers and local facilitators were involved in a deliberative planning process and community forest users groups developed a common understanding of how to apply the ACM approach. In a joint learning process the users tested assumptions built upon their experiences and knowledge which allowed them to achieve the goals of the local community in a sustainable manner. Evidence of the combined application of the ACM process and social learning are presented from six case studies on community forestry in Nepal using a broader range of the knowledge management activities. Community forest management provides a participatory environment to achieve conservation and poverty reduction. In particular, the current status, challenges, and opportunities for future improvement as seen from the perspective of social learning are highlighted. Conclusions and policy suggestions are made as contribution for the development of a common understanding in which an ACM approach can be practiced to transform a knowledge management organization towards a learning environment.
By storing Personality Traits in User Profiles we enable Recommender Systems to deduce more interesting recommendations for users acting pro-actively in order to offer them products/services as a consequence of a prediction of their future needs and behavior. This paper is proposed to improve the robustness of recommendations by using psychological aspects such as Personality Traits. This paper is a part of a PhD ongoing work.
In the paper the new possibilities of eLearning 2.0 management systems for knowledge production, experience sharing and communication are presented. The Web 2.0 effects and mechanisms for knowledge capturing and construction are discussed. Reviews of seven new generation learning systems are done with aim one of them to be selected for knowledge building and competence development during the university education as well as after degree receiving. The analysis of eLearning 2.0 management systems is performed in context of the IEEE LTSA (Learning Technology Systems Architecture) component architecture.
There is a significant gap between the services provided by dedicated information systems and general desktop systems for document communication and preparation. This situation is a serious knowledge-management problem, which often results in information loss, poor communication, and confusion among users. Semantic desktops promise to bring knowledge-based services to common desktop applications and, ultimately, to support knowledge management by adding advanced functionality to familiar computing environments. By custom tailoring these systems to different application domains, it is possible to provide dedicated services that assist users in combining document handling and communication with structured workflow processes and the services provided by dedicated systems. This paper presents a model for developing custom-tailored document processing for semantic-desktop systems. Our approach has been applied to the domain of military command and control, which as based on highly-structured document-driven processes.
A Report on a Systems Theory Based Approach to Identify Options for Higher Knowledge Work Productivity and its Applications in Business and Public Management
The established methods used for measuring labour productivity originally designed for the manufacturing sector do not fit the specific characteristics of knowledge work. We therefore propose a more appropriate understanding of the driving forces behind knowledge work productivity, focussing on process quality instead of result quantity. In a three step potential analysis, we assess (1) the knowledge intensity and then (2) current levels of knowledge work productivity with regard to typical intellectual activities such as information processing, communication, decision making, and learning, as well as organizational adaptability. The quality of knowledge work can be increased if the handling of information, communication and knowledge during these activities occurs in a systematically organised way instead of arbitrarily. Results of the analysis are then used to (3) propose both short and medium term action plans for more productive knowledge work.
The advent of information and communication technology (ICT) provides opportunities for employees with offices in geographically dispersed locations to communicate, share and collaborate on projects to achieve common business goals. This paper describes the experiences of two Romanian telecom companies, one of them have adopted distance working as a key part of its organizational strategy.
Project organizations make particular demands on the management of knowledge both within projects and across projects. In this contribution we present a method kit for the improvement of knowledge management in a project organization in the German Federal Armed Forces. The kit was developed in an interdisciplinary cooperation with the Bundeswehr University Munich. The project team approached two goals: The method kit firstly should serve as an instrument for a target-oriented identification and for removing project specific knowledge barriers. Secondly, the kit should create awareness for measures to further support knowledge work. We describe the basic elements of the method kit and present a process model for its application.
Developing successful knowledge management (KM) processes is extremely difficult. In general, a large number of all KM projects end unsuccessfully. The aim of this paper is to summarize and study the attempts to take advantage of Lessons Learned in the Swedish Armed Forces (SwAF), focusing on international missions. Relevant reports, articles and literature have been studied. With the purpose of understanding the reasons for failure and the failure factors in SwAF’s attempts at KM, Chua and Lams’ model for unsuccessful KM implementation has been applied to four cases from the organization. The results show that SwAF are aware of the importance of knowledge and have attempted to implement KM on several occasions. In most cases, however, the KM projects do not achieve widespread use and eventually end unsuccessfully. Furthermore, many of the KM tools that have been developed are no longer in use. The Swedish Explosive Ordnance Disposal and Demining Centre (SWEDEC) and the Swedish Air Force are notable exceptions.
Due to increasing professionalization and specialization in the development of computer and video games new challenges regarding the support of knowledgeintensive activities emerge. This paper aims at sensitizing and systematizing the needs and potentials for continuous integration of knowledge management into game development. It describes the interplay of development activities and involved parties with the knowledge creation process and provides insight into a tool-based approach that aims to support knowledge management in game development on three distinct levels.
In this paper, we analyze the relation of private and public information spaces in organizations and its implication for organizational knowledge management. By private information spaces, we mean all (electronic) information, which is only accessible by a single person in an organization (e.g. local files or personal E-Mails). The organizational information space in turn, consists of all electronic information, which can be accessed by all or most members of an organization. Based on this distinction, we develop a notion of information gaps between the organizational and the individual worker’s information space. We derive four basic situations and discuss the implications for organizational knowledge management in each one. We support our claims by describing results from initial evaluation studies.
Despite intensive research within the field of knowledge management and its components, the issue of knowledge valuation and its organisational integration presents a big challenge. Existing research papers about knowledge valuation have remained on very abstract levels and therefore cannot be very easily adapted to the needs of a specific company. Often only scarce information is provided for specific practical implementation. This interferes considerably with the application of existing methods of knowledge valuation. In addition, support by information technology seems only seldom to be found nowadays, which also complicates the application of existing methods in organisations. The aim of this research paper is to compare selected established approaches of knowledge valuation on the basis of certain criteria. Furthermore, an analysis and identification of possibilities for improvement are given.
Creating Profound Change and Radically New Knowledge as Core Challenges in Knowledge Management
This paper introduces an alternative approach to innovation: Emergent Innovation. As opposed to radical innovation Emergent Innovation finds a balance and integrates the demand both for radically new knowledge and at the same time for an organic development from within the organization. From a knowledge management perspective one can boil down this problem to the question of how to cope with the new and with profound change in knowledge. This question will be dealt with in the first part of the paper. As an implication the alternative approach of Emergent Innovation will be presented in the second part: this approach looks at innovation as a socio-epistemological process of “learning from the future”.