Graph-based reasoning in collaborative knowledge management for industrial maintenance

Capitalization and sharing of lessons learned play an essential role in managing the activities of industrial systems. This is particularly the case for the maintenance management, especially for distributed systems often associated with collaborative decision-making systems. Our contribution focuses on the formalization of the expert knowledge required for maintenance actors that will easily engage support tools to accomplish their missions in collaborative frameworks. To do this, we use the conceptual graphs formalism with their reasoning operations for the comparison and integration of several conceptual graph rules corresponding to different viewpoint of experts. The proposed approach is applied to a case study focusing on the maintenance management of a rotary machinery system

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

Business rules based legacy system evolution towards service-oriented architecture.

Enterprises can be empowered to live up to the potential of becoming dynamic, agile and real-time. Service orientation is emerging from the amalgamation of a number of key business, technology and cultural developments. Three essential trends in particular are coming together to create a new revolutionary breed of enterprise, the service-oriented enterprise (SOE): (1) the continuous performance management of the enterprise; (2) the emergence of business process management; and (3) advances in the standards-based service-oriented infrastructures. This thesis focuses on this emerging three-layered architecture that builds on a service-oriented architecture framework, with a process layer that brings technology and business together, and a corporate performance layer that continually monitors and improves the performance indicators of global enterprises provides a novel framework for the business context in which to apply the important technical idea of service orientation and moves it from being an interesting tool for engineers to a vehicle for business managers to fundamentally improve their businesses

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

A Rational Scheme for Conflict Detection and Resolution in Distributed Collaborative Environments for Enterprise Integration

A typical enterprise may have large numbers of information sources such as data stores, expert systems, knowledge-based systems, or standard software systems. These may need to be integrated so that, for example, an application program or a decision maker can access information from all these sources. Such architectures are generally called 'Distributed Collaborative Environments for Enterprise Integration'. A general problem in these enterprise integration architectures is that information from heterogeneous, pre-existing sources may be obsolete, incomplete, incorrect or, for many other reasons, contradictory. Thus, conflicting results may occur when the same information is requested from semantically related sources. A mechanism is required to detect and resolve these conflicts in a way that is rational to any potential client of the integration environment. This thesis lays open the design of a general mechanism for conflict detection and resolution that enables intelligent information agents to reason about contradictory information from pre-existing, heterogeneous and autonomous sources. The mechanism's theoretical basis is a framework that is drawn from evidence law, which shares some fundamental commonalities with conflict detection and resolution in enterprise integration environments. Conflict detection opens with gathering the results collected by the information retrieval process. These results may have justifications or certainty assessments attached to them. Furthermore, it identifies whether and how these results are conflicting. The design of a conflict resolution mechanism is based on a rational scheme for judging the weight of conflicting results. First, the agents assess the reliability or credibility of an information source. Judgement based on the weight of conflicting results is first applied to any available, domain-specific, resolution strategies. Second, the agent applies any 'general scientific' resolution strategies that are not specific to one domain. When no domain-related expertise can solve the conflict then the agent can only judge on domain independent evaluation criteria such as the results' reliability. A scheme is sketched out for judgement based on the reliability of conflicting results, involving three steps: Ranking the conflicting results according to their reliability; Ways to redefine conflicting results; and Heuristic decision-making. The evaluation includes a computational implementation of an enterprise integration environment incorporating a model of an information agent. An example is realised in this environment. The conflict detection and resolution mechanism, and interfaces to each integrated source, are implemented in Visual C++. A case study is conducted on this scenario to evaluate each conflict detection and resolution step. Furthermore, this illustrates both the advantages over existing approaches and the limitations

DataHub: Science data management in support of interactive exploratory analysis

The DataHub addresses four areas of significant needs: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactives nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc), in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept

Physician Incentive Management in University Hospitals: Inducing Efficient Behavior Through the Allocation of Research Facilities

The imperative to improve healthcare efficiency is now stronger than ever. Rapidly increasing healthcare demand and the prospect of healthcare cost exploding require that measures be taken to make healthcare organizations become more efficiency-aware. Alignment of organizational interests is therefore important. One of the main hurdles to overcome is the provision of the right incentives to healthcare workers, in particular physicians. In this research we investigate the incentive system for physicians in university hospitals. We present an inquiry held in a large university hospital in the Netherlands and show that non-financial incentives receive significantly more support among physicians than financial incentives. Over 95 percent of the physicians indicated they derive more work stimulus from research possibilities or scientific status than from wage. Over 80 percent of the physicians also indicated they prefer to be able to do more research. We therefore identified a broad class of non-financial incentives aimed at physicians in university hospitals: research facilities. The main tradeoff in using research facilities within an incentive system is between efficient resource utilization and inducement effects. This thesis constructs a principal-multi-agent model where agents engage in both care and research and which includes heterogeneity and private information. We study how research facilities incentives can be used to improve hospital performance if the current wage system is left intact. We show that research facilities are optimally used as incentives for both care and research activities, and that the hospital offers different contracts depending on physician ability and valuation. Moreover, if physicians need to reveal their valuations for research facilities, the hospital finds it optimal to allow physicians to make a rent. We discuss some implications of extending the theoretical results to practice

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks