Ansgar Bernardi

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.

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.

A methodological approach to supporting organizational learning

Many organizations need to respond quickly to change and their workers need to regularly develop new knowledge and skills. The prevailing approach to meeting these demands is on-the-job training, but this is known to be highly ineffective, cause stress and devalue workplace autonomy. Conversely, organizational learning is a process through which workers learn gradually in the work context through experience, reflection on work practice and collaboration with colleagues. Our approach aims to support and enhance organizational learning around enriched work representations. Work representations are tools and documents used to support collaborative working and learning. These are enriched through associations with formal knowledge models and informal discourse. The work representations, informal discourse and associated knowledge models together form on organizational memory from which knowledge can be retrieved later. Our methodological approach to supporting organizational learning is drawn from three industrial case studies concerned with machine maintenance, team planning and hotline support. The methodology encompasses development and design activities, a description of the roles and duties required to sustain the long-term use of the tools, and applicability criteria outlining the kind of organizations that can benefit from this approach.

Proactive Knowledge Delivery for Enterprise Knowledge Management

An overview of the recent trends in modern enterprises motivates the central requirements for knowledge management and its support by information technology. We illustrate proactive knowledge delivery and context-sensitive information retrieval by presenting the KnowMore system. This prototype realizes active support by providing relevant information to current tasks in enterprises which are managed by a workflow system. We identify the key concepts which need to be represented in order to deal with the existing heterogeneity. We sketch the architecture of the system and highlight some implementation details.

IdentityRank: Named Entity Disambiguation in the Context of the NEWS Project

In this paper we introduce the IdentityRank algorithm, developed as part of the EU-funded project NEWS to address the problem of named entity disambiguation in the context of semantic annotation of news items. The algorithm provides a ranking of the candidate instances within an ontology which can be associated to a certain entity. In order to do so, it uses as context the metadata available in a certain news item. The algorithm has been evaluated with promising results.

Worlds and transformations: Supporting the sharing and reuse of engineering design knowledge

Design involves the formulation of a solution, such as a product specification, from initial requirements. Design in industrial and other contexts often involves the building and use of models that allow the designer to test hypotheses and learn from possible design decisions prior to building the physical product. The building and testing of models is a design process in its own right. Previous work in knowledge management, design rationale and the psychology of design has demonstrated that designers often vary from prescriptive methodologies of the design process and have problems appropriately describing their design activity in order to support design collaboration and the reuse of design artefacts. Drawing on this work, we support design collaboration and reuse structured according to key transformational episodes in the design process and the design artefacts they produce. To support this, we characterise the design task as progressing through a series of worlds, each comprising its own concepts and vocabulary, and supported by its own design tools. The design process can then be described in terms of important transformations that are made from one world to the next. This allows a targeted approach to rationale capture integrated with work practice and associated with products of the design process. This approach has been successfully deployed and tested in two industrial engineering companies. Findings included improved collaboration in design teams, effective reuse and improved training for new members of the design team. This work has more general implications for the development of design rationale methods and tools to support the design process.

ARC-TEC : acquisition, representation and compilation of technical knowledge

A global description of an expert system shell for the domain of mechanical engineering is presented. The ARC-TEC project constitutes an AI approach to realize the CIM idea. Along with conceptual solutions, it provides a continuous sequence of software tools for the acquisition, representation and compilation of technical knowledge. The shell combines the KADS knowledge-acquisition methodology, the KL-ONE representation theory and the WAM compilation technology. For its evaluation a prototypical expert system for production planning is developed. A central part of the system is a knowledge base formalizing the relevant aspects of common sense in mechanical engineering. Thus, ARC-TEC is less general than the CYC project but broader than specific expert systems for planning or diagnosis.

FEAT-REP : representing features in CAD/CAM

When CAD/CAM experts view a workpiece, they perceive it in terms of their own expertise. These terms, called features, which are build upon a syntax (geometry) and a semantic (e.g. skeletal plans in manufacturing or functional relations in design), provide an abstraction mechanism to facilitate the creation, manufacturing and analysis of workpieces. Our goal is to enable experts to represent their own feature-language via a feature-grammar in the computer to build feature-based systems e.g. CAPP systems. The application of formal language terminology to the feature definitions facilitates the use of well-known formal language methods in conjunction with our flexible knowledge representation formalism FEAT-REP which will be presented in this paper.

Big Data Analysis of Manufacturing Processes

The high complexity of manufacturing processes and the continuously growing amount of data lead to excessive demands on the users with respect to process monitoring, data analysis and fault detection. For these reasons, problems and faults are often detected too late, maintenance intervals are chosen too short and optimization potential for higher output and increased energy efficiency is not sufficiently used. A possibility to cope with these challenges is the development of self-learning assistance systems, which identify relevant relationships by observation of complex manufacturing processes so that failures, anomalies and need for optimization are automatically detected. The assistance system developed in the present work accomplishes data acquisition, process monitoring and anomaly detection in industrial and agricultural processes. The assistance system is evaluated in three application cases: Large distillation columns, agricultural harvesting processes and large-scale sorting plants. In this paper, the developed infrastructures for data acquisition in these application cases are described as well as the developed algorithms and initial evaluation results.

Leveraging passive paper piles to active objects in personal knowledge spaces

Office workers tend to produce paper piles of documents to read or to process sometime later. The information contained in these piles is often lost if it is not transferred to electronic format and connected to knowledge structures. Information that is not part of the knowledge worker’s electronic information space is frequently overlooked because it is not proactively provided during actual processes or tasks he is involved in. This paper presents a novel prototype for an intelligent office appliance, which results from an integration of three state-of-the-art office applications/appliances: a workflow system, a document classification system, and a multi-functional peripheral. The resulting system allows for leveraging an office worker’s papers to her personal knowledge space in order to realize a pro-active and context-sensitive information support within knowledge-intensive tasks and processes.