How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Organizational learning II: Theory, method and practice

Knowledge Management

An ontology is a formal description of concepts and relationships that can exist for a community of human and/or machine agents. The notion of ontologies is crucial for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies considering ontology languages, ontology engineering methods, example ontologies, infrastructures and technologies for ontologies, and how to bring this all into ontology-based infrastructures and applications that are among the best of their kind. The field of ontologies has tremendously developed and grown in the five years since the first edition of the "Handbook on Ontologies". Therefore, its revision includes 21 completely new chapters as well as a major re-working of 15 chapters transferred to this second edition.

Handbook on Ontologies

Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification framework of context-aware systems, and explore each feature of classification framework. This paper is based on a literature review of context-aware systems from 2000 to 2007 using a keyword index and article title search. The classification framework is developed based on the architecture of context-aware systems, which consists of the following five layers: concept and research layer, network layer, middleware layer, application layer and user infrastructure layer. The articles are categorized based on the classification framework. This paper allows researchers to extract several lessons learned that are important for the implementation of context-aware systems.

Context-aware systems

In this paper we will give an overview of the Semantic Desktop paradigm, beginning with the history of the term, a definition, current work and its relevance to knowledge management of the future. Existing applications and research results are listed and their role as building blocks of the future Semantic Desktop described. Based on the analysis of existing systems we propose two software architecture paradigms, one for the Semantic Desktop at large and another for applications running on a Semantic Desktop. A view on the context aspect of the Semantic Desktop and the Knowledge Management aspect is given. Based on the current events and projects, we give an outlook on the next steps.

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Overview and outlook on the semantic desktop

From an IT point of view, a key objective of successful knowledge management is to provide relevant and necessary information at the right time to support humans in accomplishing their tasks. This paper presents a prototypical system which meets this objective in an enterprise environment. Based on context information associated with the enterprise’s business processes, an integration of workflow engine and information assistant enables active presentation of relevant information to the user. We describe the functionality of the system and elaborate (i) on necessary extensions to the business process models, (ii) the ontologies used for information modeling, and (iii) the integration of workflow engine and active information assistant. The prototype system has been developed in the KnowMore project of the DFKI Knowledge Management Group.

Context-Aware, Proactive Delivery of Task-Specific Information: The KnowMore Project

Knowledge work cannot typically be modeled sufficiently by classical, static process models. To enable a process-oriented knowledge management (KM) approach under these circumstances, the concept of weakly-structured workflows has been developed. This approach intertwines process modeling and workflow enactment and facilitates active information support in dynamically changing environments. Furthermore, the approach allows process knowledge itself to be used as a valuable resource in KM. In order to investigate whether this approach is viable and useful for supporting knowledge-intensive activities we designed and performed a comprehensive experimental evaluation. We outline the conceptual approach and realization in an agent-based software framework for organizational memories and describe the experimental settings. The results of the experiment demonstrate the viability of our key concepts.

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Weakly-structured workflows for knowledge-intensive tasks: an experimental evaluation

Comprehensive approaches to knowledge management in modern enterprises are confronted with scenarios which are heterogeneous, distributed, and dynamic by nature. Pro-active satisfaction of information needs across intra-organizational boundaries requires dynamic negotiation of shared understanding and adaptive handling of changing and ad-hoc task contexts. In this paper, we present the notion of a Distributed Organizational Memory (DOM) as a meta-information system with multiple ontology-based structures and a workflow-based context representation. We argue that agent technology offers the software basis which is necessary to realize DOM systems. We sketch a comprehensive Framework for Distributed Organizational Memories which enables the implementation of scalable DOM solutions and supports the principles of agent-mediated knowledge management. 1 DISTRIBUTED ORGANIZATIONAL MEMORIES Knowledge Management envisions the comprehensive use of an enterprise's knowledge, whoever acquired it, wherever it is stored and however it is formulated in particular. Organizational Memory Information Systems shortly Organizational Memories, OMs shall support the effective handling, conservation, and use of knowledge across time and space and as far as possible in person-independent ways. An OM comprises a variety of information sources where information elements of all kinds, structures, contents, and media types are available. The OM has to control and access these information sources in accordance with the users’ information needs, which are determined by a combination of personal, organizational and contextual circumstances: The useful interaction with the OM is influenced by the actual task at hand, but also by the individual’s role in the organization, his personal skills and interest profiles (and their overlap with the requirements of the current activity), as well as by prior knowledge and experience. The internal structure of an OM reflects this principle: By representing explicit interconnections between information elements and formalized models (particularly the domain, the enterprise, and the work context) the content of the information elements is partially made available to automatic processing and reasoning. As the various models form a basis for common reference across an enterprise, ranging from lists of shared vocabulary to more detailed ontological representations, common and shared understanding is supported by this approach. An explicit modelling of business processes as a means for context representation facilitates the situation-specific mark-up and retrieval of information elements; the integration with workflow systems which enact the process models enables pro-active information services. Consequently, an OM is best described as a metainformation system with tight integration into enterprise business processes, which relies on appropriate formal models and ontologies as a basis for common understanding and automatic processing capabilities (Figure 1; Abecker et al., 1998 & 2000). This description seems to motivate a central approach, and in fact a number of OM systems were realized as central repositories with globally valid ICEIS 2003 Artificial Intelligence and Decision Support Systems 4 ontologies and structures. However, centralized OM approaches have drawbacks with respect to two important aspects: a) Knowledge generation and use in an enterprise is distributed by nature. Departments, groups and individual experts develop individual, differing views on given subjects. These views are motivated and justified by the particularities of the actual work, goals, and situation. Obtaining a single, globally agreed-upon vocabulary on a level of detail which is sufficient for all participants is very expensive or even outright impossible. Consequently, an OM should benefit from balancing both local expertise – which might represent knowledge which is not easily shareable on a global level–and overall views on a more global level. A strictly centralized approach neglects this opportunity. b) Knowledge resides in changing environments. A centralized OM is ill-suited to deal with continuous modifications in the enterprise: The maintenance costs for its detailed models and ontologies simply get too high. Furthermore, centralized OMs assume a strict sequence of design, implementation, and use, while in reality a more evolutionary approach seems more promising: OM-like structures evolve in different groups and departments, using appropriate formalizations and conceptualizations. Integrating these elements under a common roof without disturbing their individual value should result in solutions which offer common benefit with reduced efforts while reaching better acceptance on the individual level. The reality of enterprises' environments thus asks for a distributed approach to OM realization: Distributed, heterogeneous OM cells let local expertise prevail while striving for maximal integrated benefit. Evolutionary growth and scalability on all levels is reached by allowing individual OM cells to grow and mature independently while interaction and communication brings enterprise-wide exchange and understanding. The natural approach for building complex software representations of distributed scenarios is agent technology. In the following, we will outline the characteristics of software agents which are helpful for Distributed Organizational Memories (DOM). We will argue that a comprehensive framework for DOMs requests the notion of agent societies. Further, an overview of typical instantiations of agents within the framework is given. 2 AGENT INFRASTRUCTURE FOR THE DOM 2.1 Agent-based Software Systems The DOM scenario is obviously characterized by a high degree of heterogeneity and distributedness, it can easily lead to a highly complex software system, and it is an open environment in the sense that we have to expect that frequently new components (even formerly unknown ones) may be plugged into the overall system, be replaced by other modules, or plugged out. Over the last years, the paradigm of agent-based computing turned out to be an appropriate means for dealing with such application scenarios. In this paper, we suppose the reader to have basic knowledge about agent-based software systems and engineering. We employ the “weak definition” of agents introduced in (Wooldridge & Jennings, 1995) with the following definitional features: (i) autonomy; (ii) social ability; (iii) reactive behaviour; and (iv) pro-active behaviour. Other possible characteristics of software agents like some level of intelligence, mobility, or techniques for learning and adaptation may also be relevant for parts of the overall solution we aim at. However, in this paper we will focus on multiagent systems’ capabilities for selforganization and social organization as a means for dealing with complex and dynamically changing situations which are mainly constituted by the characteristics mentioned above. In principle, human as well as software agents can be described with respect to the following dimensions corresponding to Newell’s (1982) knowledge level: Goals: Agents operate in a regularly changing environment. In doing so, they not only react to such changes, but also have their own goals and objectives which they try to achieve. Figure 1: OM as a Meta-Information System AGENT TECHNOLOGY FOR DISTRIBUTED ORGANIZATIONAL MEMORIES 5 Knowledge: Agents have knowledge with respect to the relevant realms of their environment, e.g. objects and other agents, as well as with respect to their own goals. Competencies: An agent’s abilities to perceive and manipulate its environment and its own internal state. In a multi-agent environment, the abilities to communicate with other actors are particularly important. Through communication, knowledge about facts, goals, competencies, etc. can be exchanged. This allows for negotiation and agreements which may lead to a distribution of tasks between agents or to changes of an agent's knowledge and goals. 2.2 Socially-Enabled Software Agents In Section 3 we will show that for a fully agent-based realization of the DOM scenario a huge amount of agents with possibly diverging goals and maybe highly complex communication and negotiation threads is required. As discussed in much detail by (Schillo et al., 2002), optimal work distribution and collaborative performance in such a group of agents benefits not only from task delegation and knowledge exchange, but also from social delegation as the basis for dynamic self-organization of agent societies, in order to achieve optimal group performance, yet staying flexible enough to cope with changing requirements. Via social delegation, groups of agents constitute Agent Societies with less communication effort because of clear responsibilities, with better task distribution because of specialization, etc. The phenomenon of society creation and self-organization can be observed in sociology (Bourdieu & Wacquant, 1992) and is a major topic of organizational theory. (Castelfranchi, 2000) considers it a crucial point for the introduction of agents into Enterprise Information Systems to complement the mechanisms for bottom-up control (system behaviour emerges from goals and negotiation at the micro level), which are inherent to the agent paradigm, by new mechanisms which appropriately reflect the global directives to be propagated top-down in a stable organization. In order to achieve this goal, we propose to build a DOM as a set of collaborating societies of sociallyenabled agents. These notions are being further refined in (Vicinus, 2002) and are exemplarily illustrated in (Elst & Abecker, 2002). In this paper we sketch the conceptual foundations and sketch their application in the DOM. Hence we define an Agent Society as a set of agents (an agent can be member of several societies at the same time) with at least one manager agent (which administers membership, role assig

Agent Technology for Distributed Organizational Memories: The Frodo Project.

Knowledge work processes consist of interleaved agile, weakly-structured processes and strictly-structured processes. Knowledge management approaches for weakly-structured, ad-hoc knowledge work processes need to be lightweight, i.e., they cannot rely on high upfront modeling effort. However, approaches for business process- oriented knowledge management require intensive modeling activities. In this paper, we introduce a bottom-up strategy for proactive information delivery to cover the complete spectrum of knowledge work processes in different phases, and present a series of prototypes realizing selected phases of this strategy. Among these is a novel prototype for supporting weakly-structured processes by integrating a standard to-do list application with a state-of-the-art document classification system. The resulting system allows for a task-oriented view on an office worker's personal knowledge space in order to realize a proactive and context-sensitive information support during her daily, knowledge-intensive tasks.

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Ansgar Bernardi

Papers

Overview and outlook on the semantic desktop

Context-Aware, Proactive Delivery of Task-Specific Information: The KnowMore Project

Weakly-structured workflows for knowledge-intensive tasks: an experimental evaluation

Agent Technology for Distributed Organizational Memories: The Frodo Project.

From Lightweight, Proactive Information Delivery to Business Process-Oriented Knowledge Management