Andreas Abecker

Toward a technology for organizational memories

To meet the growing need for enterprise-wide knowledge management, the authors have developed and fielded a three-layered model for processing knowledge. This article shows how their organizational memory serves as an intelligent assistant and deals with both formal and non-formal knowledge elements in a task-oriented fashion.

Corporate Memories for Knowledge Management in Industrial Practice: Prospects and Challenges

A core concept in discussions about technological support for knowledge management is the Corporate Memory. A Corporate or Organizational Memory can be characterized as a comprehensive computer system which captures a company’s accumulated know-how and other knowledge assets and makes them available to enhance the efficiency and effectiveness of knowledge-intensive work processes. The successful development of such a system requires a careful analysis of established work practices and available information-technology (IT) infrastructure. This is essential for providing a cost-effective solution which will be accepted by the users and can be evolved in the future. This chapter compares and summarizes our experiences from three case studies on Corporate Memories for supporting various aspects in the product life-cycles of three European corporations. Based on the conducted analyses and prototypical implementations, we sketch a general framework for the development methodology, architecture, and technical realization of a Corporate Memory.

The role of ontologies in autonomic computing systems

The goal of IBMs autonomic computing strategy is to deliver information technology environments with improved self-management capabilities, such as self-healing, self-protection, self-optimization, and self-configuration. Data correlation and inference technologies can be used as core components to build autonomic computing systems. They can also be used to perform automated and continuous analysis of enterprise-wide event data based upon user-defined configurable rules, such as those intended for detecting threats or system failures. Furthermore, they may trigger corrective actions for protecting or healing the system. In this paper, we discuss the use of ontologies as a high-level, expressive, conceptual modeling approach for describing the knowledge upon which the processing of a correlation engine is based. The introduction of explicit models of state-based information technology resources into the correlation technology approach allows the construction of autonomic computing systems that are capable of dealing with policy-based goals on a higher abstraction level. We demonstrate some of the benefits of this approach by applying it to a particular IBM implementation, the eAutomation correlation engine.

Information supply for business processes: coupling workflow with document analysis and information retrieval

Explicit modeling of business processes and their enactment in workflow systems have proved to be valuable in increasing the efficiency of work in organizations. We argue that enacted business processes — i.e. workflow management systems — form a solid basis for adequate information support in complex and knowledge-intensive business processes. To support this claim we demonstrate results from two different projects. The VirtualOffice approach employs workflow-context information to support high-precision document analysis and understanding in standard office settings; the combination of workflow context and document analysis allows for the automatic handling of incoming paper mail with respect to the appropriate workflows. The KnowMore approach focuses on the support of people who work on knowledge-intensive tasks by automatic delivery of relevant and goal-specific information. To this end, workflow context, an extended process model, and a detailed modeling of information sources are combined.

Agent-Mediated Knowledge Management

Knowledge Management (KM) is a systematic approach for sustainably improving the handling of knowledge on all levels of an organization (individual, group, organizational, and inter-organizational level) in order to support the organization’s business goals, such as innovation, quality, cost effectiveness etc. KM holistically combines activities adressing organization culture, static and dynamic organization structures, as well as ICT infrastructure (cp. [4]). ICT approaches typically fall into one of two basic system classes: One class—comprising, e.g., Organizational Memory Information Systems (OMs, cp. [1, 20])—aims at acquisition, structuring and high–precision delivery of explicit knowledge (“provide the right people with the right information at the right time”). The other class of systems—like expert finder systems or community of practice support—doesn’t rely so much on explicitly represented knowledge, but rather brings people together, for instance, to solve a given knowledge– intensive problem (see, for instance [6, 24]). Based on our practical and research experience with KM solutions, we identify the following requirements as central challenges for next generation KM systems. We can only sketch them briefly, for more detail, please refer to [38, 26]. R1: KM has to respect the distributed nature of knowledge in organizations: A KM system should therefore allow to balance between (a) global knowledge which might have or might constitute a shared context, but may also be relatively expensive; and (b) local expertise which might represent knowledge that is not easily shareable or is not worth sharing. Further, as global views cannot always be reached, a KM system must be able to handle context switches of knowledge assets, e.g., by providing explicit procedures for capturing the context during knowledge acquisition and for re-contextualizing during knowledge support. Fully accepting the ideas of distribudness means to face technical as well as organizational problems such as trust, responsibility, and contextuality. R2: KM systems must reflect the inherent goal dichotomy between business processes and KM processes.: Within an environment of bounded resources, knowledge workers will always concentrate on their first order business processes instead of KM meta processes. This means they optimize

Ontologies for Knowledge Management

Within Computer Science and Artificial Intelligence, the term ontologies was coined in the Knowledge Sharing and Reuse Effort, for efficient engineering of (distributed, cooperating) knowledge-based systems. It is not surprising that it soon entered the Knowledge Management (KM) area: Sharing and reuse of personal, group, and organizational knowledge are among the central goals aimed at in most KM projects. In this chapter we introduce the main ideas of KM, as well as the role of and requirements for information technology (IT) in KM. We discuss the potential of ontologies as elements in IT support for KM. We characterize their current role in research and practice, derive a working focus for the near future, and conclude with an outlook on trends in KM software and their implications on ontologies.

Towards Agent-Mediated Knowledge Management

In this paper, we outline the relation between Knowledge Management (KM) as an application area on the one hand, and software agents as a basic technology for supporting KM on the other. We start by presenting characteristics of KM which account for some drawbacks of today’s – typically centralized – technological approaches for KM. We argue that the basic features of agents (social ability, autonomy, re- and proactiveness) can alleviate several of these drawbacks. A classification schema for the description of agent-based KM systems is established, and a couple of example systems are depicted in terms of this schema. The paper concludes with questions which we think research in Agent-mediated Knowledge Management (AMKM) should deal with.

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

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 enterprises 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.

Ontologies for information management: balancing formality, stability, and sharing scope

Abstract Ontologies are an emerging paradigm to support declarativity, interoperability, and intelligent services in many areas, such as Agent-based Computation, Distributed Information Systems, and Expert Systems. Inspired by the definition of ‘ontology’, we discuss three dimensions of information that have fundamental impact on the usefulness of ontologies for information management: formality, stability, and sharing scope of information. We briefly sketch some techniques, which are suited to find a balance (in terms of cost-benefit ratio) in each of these dimensions when building and using ontology-based information systems. We characterize roles of ontology-related actors with respect to goals, knowledge, competencies, rights, and obligations. These roles allow to form ontology societies where specific mechanisms and processes can be installed to stabilize a steady state in the three dimensions discussed. The practical use of our approach is shown in the scenario of a distributed Organizational Memory architecture.

Transforming E-government and E-participation through IT

This paper dealt with the topic of E-government and E-participation aiming to provide the technologies and tools for more efficient public administration systems and more participatory decision processes. Public administrations are considered the heaviest service industry worldwide. During the last decades, governments all over the world have undertaken huge investments in information and communication technologies (ICT), but they are still far from satisfying their constituents, as they usually operate inefficiently and ineffectively. E-government and E-participation research aims to refocus government on its customers-citizens and businesses and provide the models, technologies, and tools for more effective and efficient public administration systems as well as more participatory decision processes.