Knowledge re-use for decision support

Effective decision support has already been identified as a fundamental requirement for the realisation of Network Enabled Capability. Decision making itself is a knowledge-intensive process, and it is known that right decisions can only be reached based on decision maker's good judgement, which in turn is based on sufficient knowledge. It is not unusual for decision makers to make incorrect decisions because of insufficient knowledge. However, it is not always possible for decision makers to have all the knowledge needed for making decisions in complex situations without external support. The re-use of knowledge has been identified as providing an important contribution to such support, and this paper considers one, hitherto unexplored, aspect of how this may be achieved. This paper is concerned with the computational view of knowledge re-use to establish an understanding of a knowledge-based system for decision support. The paper explores knowledge re-use for decision support from two perspectives: knowledge provider's and knowledge re-user's. Key issues and challenges of knowledge re-use are identified from both perspectives. A structural model for knowledge re-use is proposed with initial evaluation through empirical study of both experienced and novice decision maker's behaviour in reusing knowledge to make decisions. The proposed structural model for knowledge re-use captures five main elements (knowledge re-uers, knowledge types, knowledge sources, environment, and integration strategies) as well as the relationships between the elements, which forms a foundation for constructing a knowledge-based decision support system. The paper suggests that further research should be investigating the relationship between knowledge re-use and learning to achieve intelligent decision support

Managing knowledge in the context of sustainable construction

The 21st century has been a growing awareness of the importance of the sustainability agenda. Moreover for construction, it has become increasingly important as clients are pushing for a more sustainable product to complement their organisations’ own strategic plans. Sustainable development can be defined as development that meets the needs of the present without compromising the ability of future generations to meet their needs. Sustainable construction is therefore seen as the application of sustainable practices to the activities of the construction sector. One of the key factors in making construction projects more sustainable is overcoming the obstacles of capturing and managing the knowledge required by project teams to effect such change. Managing this knowledge is key to the construction industry because of the unique characteristics of its projects, i.e. multi-disciplinary teams, dynamic participation of team members, heavy reliance on previous experiences/heuristics, the one-off nature of the projects, tight schedules, limited budget, etc. Initiatives within the industry and academic research are developing mechanisms and tools for managing knowledge in construction firms and projects. Such work has so far addressed the issues of capturing, storing, and transferring knowledge

Encapsulating and representing the knowledge on the evaluation of an engineering system

This paper proposes a cross-disciplinary methodology for a fundamental question in product development: How can the innovation patterns during the evolution of an engineering system (ES) be encapsulated, so that it can later be mined through data mining analysis methods? Reverse engineering answers the question of which components a developed engineering system consists of, and how the components interact to make the working product. TRIZ answers the question of which problem-solving principles can be, or have been employed in developing that system, in comparison to its earlier versions, or with respect to similar systems. While these two methodologies have been very popular, to the best of our knowledge, there does not yet exist a methodology that reverseengineers and encapsulates and represents the information regarding the complete product development process in abstract terms. This paper suggests such a methodology, that consists of mathematical formalism, graph visualization, and database representation. The proposed approach is demonstrated by analyzing the design and development process for a prototype wrist-rehabilitation robot

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages

The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)

Towards a pragmatic approach for dealing with uncertainties in water management practice

Management of water resources is afflicted with uncertainties. Nowadays it is facing more and new uncertainties since pace and dimension of changes (e.g. climatic, demographic) are accelerating and are likely to increase even more in the future. Hence it is crucial to find pragmatic ways to deal with these uncertainties in water management. So far, decision-making under uncertainty in water management is based on either intuition, heuristics and experience of water managers or on expert assessments all of which are only of limited use for water managers in practice. We argue for an analytical yet pragmatic approach to enable practitioners to deal with uncertainties in a more explicit and systematic way and allow for better informed decisions. Our approach is based on the concept of framing, referring to the different ways in which people make sense of the world and of the uncertainties. We applied and tested recently developed parameters that aim to shed light on the framing of uncertainty in two sub-basins of the Rhine. We present and discuss the results of a series of stakeholder interactions in the two basins aimed at developing strategies for improving dealing with uncertainties. The strategies are synthesized in a cross-checking list based on the uncertainty framing parameters as a hands-on tool for systematically identifying improvement options when dealing with uncertainty in water management practice. We conclude with suggestions for testing the developed check-list as a tool for decision aid in water management practice. Key words: water management, future uncertainties, framing of uncertainties, hands-on decision aid, tools for practice, robust strategies, social learnin