643 research outputs found

    REST and Linked Data: a match made for domain driven development?

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    At a first glance there might appear to be an obvious alignment and overlap between the approaches prescribed by REST and Linked Data. On more detailed inspection divergences in scope and applicability present themselves, and for some aspects, incompatibility. In this paper we investigate these similarities and differences and suggest the coupling is worthy of a third look: in combination as a flexible environment in which the developer can focus on domain driven applications

    Specification of high-level application programming interfaces (SemSorGrid4Env)

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    This document defines an Application Tier for the SemsorGrid4Env project. Within the Application Tier we distinguish between Web Applications - which provide a User Interface atop a more traditional Service Oriented Architecture - and Mashups which are driven by a REST API and a Resource Oriented Architecture. A pragmatic boundary is set to enable initial development of Web Applications and Mashups; as the project progresses an evaluation and comparison of the two paradigms may lead to a reassessment of where each can be applied within the project, with the experience gained providing a basis for general guidelines and best practice. Both Web Applications and Mashups are designed and delivered through an iterative user-centric process; requirements generated by the project case studies are a key element of this approach

    Exploiting Synergy Between Ontologies and Recommender Systems

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    Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

    Sawyer-type inequalities for Lorentz spaces

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    The Hardy-Littlewood maximal operator M satisfies the classical Sawyer-type estimate ∥Mfv∥L1,∞(uv)≤Cu,v‖f‖L1(u),where u∈ A1 and uv∈ A∞. We prove a novel extension of this result to the general restricted weak type case. That is, for p> 1 , u∈ApR, and uvp∈ A∞, ∥Mfv∥Lp,∞(uvp)≤Cu,v‖f‖Lp,1(u).From these estimates, we deduce new weighted restricted weak type bounds and Sawyer-type inequalities for the m-fold product of Hardy-Littlewood maximal operators. We also present an innovative technique that allows us to transfer such estimates to a large class of multi-variable operators, including m-linear Calderón-Zygmund operators, avoiding the A∞ extrapolation theorem and producing many estimates that have not appeared in the literature before. In particular, we obtain a new characterization of ApR. Furthermore, we introduce the class of weights that characterizes the restricted weak type bounds for the multi(sub)linear maximal operator M, denoted by APR, establish analogous bounds for sparse operators and m-linear Calderón-Zygmund operators, and study the corresponding multi-variable Sawyer-type inequalities for such operators and weights. Our results combine mixed restricted weak type norm inequalities, ApR and APR weights, and Lorentz spaces

    Exploiting synergy between ontologies and recommender systems

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    Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

    Issues for the sharing and re-use of scientific workflows

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    In this paper, we outline preliminary findings from an ongoing study we have been conducting over the past 18 months of researchers’ use of myExperiment, a Web 2.0-based repository with a focus on social networking around shared research artefacts such as workflows. We present evidence of myExperiment users’ workflow sharing and re-use practices, motivations, concerns and potential barriers. The paper concludes with. a discussion of the implications of these our findings for community formation, diffusion of innovations, emerging drivers and incentives for research practice, and IT systems design

    A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines

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    The concept of social machines is increasingly being used to characterise various socio-cognitive spaces on the Web. Social machines are human collectives using networked digital technology which initiate real-world processes and activities including human communication, interactions and knowledge creation. As such, they continuously emerge and fade on the Web. The relationship between humans and machines is made more complex by the adoption of Internet of Things (IoT) sensors and devices. The scale, automation, continuous sensing, and actuation capabilities of these devices add an extra dimension to the relationship between humans and machines making it difficult to understand their evolution at either the systemic or the conceptual level. This article describes these new socio-technical systems, which we term Cyber-Physical Social Machines, through different exemplars, and considers the associated challenges of security and privacy.Comment: 14 pages, 4 figure

    Methodology for Designing Decision Support Systems for Visualising and Mitigating Supply Chain Cyber Risk from IoT Technologies

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    This paper proposes a methodology for designing decision support systems for visualising and mitigating the Internet of Things cyber risks. Digital technologies present new cyber risk in the supply chain which are often not visible to companies participating in the supply chains. This study investigates how the Internet of Things cyber risks can be visualised and mitigated in the process of designing business and supply chain strategies. The emerging DSS methodology present new findings on how digital technologies affect business and supply chain systems. Through epistemological analysis, the article derives with a decision support system for visualising supply chain cyber risk from Internet of Things digital technologies. Such methods do not exist at present and this represents the first attempt to devise a decision support system that would enable practitioners to develop a step by step process for visualising, assessing and mitigating the emerging cyber risk from IoT technologies on shared infrastructure in legacy supply chain systems

    Hypermedia by coincidence

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    We introduce an approach to linking hypermedia documents dynamically in a decentralised, peer-to-peer manner using resources that are available by coincidence, without explicit configuration. The particular approach presented utilises an open platform in combination with Distributed Link Service technology enabling dynamic hypertext generation
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