71,531 research outputs found

    Access to recorded interviews: A research agenda

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    Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

    Implementing a resource list management system in an academic library

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    Purpose – The purpose of this paper is to review the key components of the introduction of a new resource list management system (RLMS) at Nottingham Trent University (NTU) using the Aspire application from Talis Education. It explains the key service goals; the implementation milestones; the main technical challenges which needed to be addressed; and the dynamic relationship between the rollout of the RLMS and existing selection, acquisition and resource delivery processes

    Improving the translation environment for professional translators

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    When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project

    The Semantic Grid: A future e-Science infrastructure

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    e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid

    The use of non-intrusive user logging to capture engineering rationale, knowledge and intent during the product life cycle

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    Within the context of Life Cycle Engineering it is important that structured engineering information and knowledge are captured at all phases of the product life cycle for future reference. This is especially the case for long life cycle projects which see a large number of engineering decisions made at the early to mid-stages of a product's life cycle that are needed to inform engineering decisions later on in the process. A key aspect of technology management will be the capturing of knowledge through out the product life cycle. Numerous attempts have been made to apply knowledge capture techniques to formalise engineering decision rationale and processes; however, these tend to be associated with substantial overheads on the engineer and the company through cognitive process interruptions and additional costs/time. Indeed, when life cycle deadlines come closer these capturing techniques are abandoned due the need to produce a final solution. This paper describes work carried out for non-intrusively capturing and formalising product life cycle knowledge by demonstrating the automated capture of engineering processes/rationale using user logging via an immersive virtual reality system for cable harness design and assembly planning. Associated post-experimental analyses are described which demonstrate the formalisation of structured design processes and decision representations in the form of IDEF diagrams and structured engineering change information. Potential future research directions involving more thorough logging of users are also outlined

    Strategic Knowledge Measurement and Management

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    Knowledge and intellectual capital are now recognized as vital resources for organizational survival and competitive advantage. A vast array of knowledge measures has evolved, spanning many disciplines. This chapter reviews knowledge measures focusing on groups of individuals (such as teams, business and organizations), as they reflect the stock or flow of knowledge, as well as enabling processes that enhance knowledge stocks and flows. The chapter emphasizes the importance of organizational value chains, pivotal talent pools and the link between knowledge and competitive success, in understanding the significance of today’s knowledge measures, and opportunities for future research and practice to enhance them

    Traceability system for capturing, processing and providing consumer-relevant information about wood products: System solution and its economic feasibility

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    Current research and practice reports indicate the existence of purchase barriers concerning eco-friendly products, e.g. wood products. These can be ascribed to consumers' mistrust regarding the non-observable environmental impact of wood products. To counter the mistrust, wood products are commonly endowed with eco-labels, which may be perceived mostly as a marketing tool, therefore not fulfilling their intended purpose. Current studies have shown that providing consumers with wood product information based on traceability systems increases product trust and purchase intentions, with those information items most valued by consumers being identified as well. Based on this, the paper proposes a traceability information system for the capturing, processing, and provision of product information using examples of wood furniture. Furthermore, a cost-benefit model for the proposed solution is developed. The calculations indicate the possibility of implementing traceability at the item level based on a four-layer system architecture enabling the capture and delivery of all information valued by consumers at acceptable costs. The proposed system helps to overcome purchase barriers of eco-friendly products, increasing consumers' product trust and purchase intentions

    Analysis and control of complex collaborative design systems

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    This paper presents a novel method for modelling the complexity of collaborative design systems based on its analysis and proposes a solution to reducing complexity and improving performance of such systems. The interaction and interfacing properties among many components of a complex design system are analysed from different viewpoints and then a complexity model for collaborative design is established accordingly. In order to simplify complexity and improve performance of collaborative design, a general solution of decomposing a whole system into sub-systems and using unified interface mechanism between them has been proposed. This proposed solution has been tested with a case study. It has been shown that the proposed solution is meaningful and practical

    Neurocognitive Informatics Manifesto.

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    Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

    Linking Quality Attributes and Constraints with Architectural Decisions

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    Quality attributes and constraints are among the main drivers of architectural decision making. The quality attributes are improved or damaged by the architectural decisions, while restrictions directly include or exclude parts of the architecture (for example, the logical components or technologies). We can determine the impact of a decision of architecture in software quality, or which parts of the architecture are affected by a constraint, but the difficult problem is whether we are respecting the quality requirements (requirements on quality attributes) and constraints with all the architectural decisions made. Currently, the common practice is that architects use their own experience to design architectures that meet the quality requirements and restrictions, but at the end, especially for the crucial decisions, the architect has to deal with complex trade-offs between quality attributes and juggle possible incompatibilities raised by the constraints. In this paper we present Quark, a computer-aided method to support architects in software architecture decision making
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