Collaboration Enabling Internet Resource Collection-Building Software and Technologies

Over the last decade the Library of the University of California, Riverside and its collaborators have developed a number of systems, service designs, and projects that utilize innovative technologies to foster better Internet finding tools in libraries and more cooperative and efficient effort in Internet link and metadata collection building. The open-source software and projects discussed represent appropriate technologies and sustainable strategies that we believe will help Internet portals, digital libraries, virtual libraries, library catalogs-with-portal-like-capabilities (IPDVLCs), and related collection-building efforts in academia to better scale and more accurately anticipate and meet the needs of scholarly and educational users.published or submitted for publicatio

Coping with Poorly Understood Domains: the Example of Internet Trust

The notion of trust, as required for secure operations over the Internet, is important for ascertaining the source of received messages. How can we measure the degree of trust in authenticating the source? Knowledge in the domain is not established, so knowledge engineering becomes knowledge generation rather than mere acquisition. Special techniques are required, and special features of KBS software become more important than in conventional domains. This paper generalizes from experience with Internet trust to discuss some techniques and software features that are important for poorly understood domains

Towards reframing professional expert support

The paper addresses practical ways of reconfiguring professional expertise in development practice in moving away from the expert as a technocrat. Two projects associated with managing natural resource dilemmas suggest an alternative way of framing intervention involving professional experts providing a more appropriate collaborative learning space for development practice. The paper describes the heuristic devices generated by each project as helpful in bringing out dialectic tensions between practice and understanding, and between systems of interest and situations of interest (or situated problems). Firstly, SLIM (social learning for the integrated management and sustainable use of water at catchment scale) - a European Framework Programme 5 project - exemplifies social learning as a measure of sustainable development. The heuristic illustrates the dependence of sustainability on changes in practice and understanding amongst professionals and other stakeholders as part of concerted - rather than merely individual or even collective - action. Secondly, ECOSENSUS (Electronic/Ecological Collaborative Sensemaking Support System) - a Guyana focused intervention involving several UK universities in collaboration with the University of Guyana and Amerindian community representatives from the North Rupununi wetlands - builds on the SLIM heuristic in supporting the development of practice. Additionally, the ECOSENSUS heuristic provides conceptual space for the interaction between conceptual constructs of distributed stakeholders (that is, systems thinking) including those with professional expertise, and the actual context of intervention (the situated problem). Both SLIM and ECOSENSUS provide heuristics for process-orientated management enabling more meaningful and purposeful interaction between professional/ technical experts and other stakeholders, as an alternative to conventional project-orientated management intervention. An alternative framing may help to steer practice away from the apoliticised comforting linearity of professionalised systematic project management towards more constructive systemic endeavours involving multiple stakeholders

Computational aerodynamics and artificial intelligence

The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics