89,270 research outputs found

    Collaboration Enabling Internet Resource Collection-Building Software and Technologies

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    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

    INSPIRAL: investigating portals for information resources and learning. Final project report

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    INSPIRAL's aims were to identify and analyse, from the perspective of the UK HE learner, the nontechnical, institutional and end-user issues with regard to linking VLEs and digital libraries, and to make recommendations for JISC strategic planning and investment. INSPIRAL's objectives -To identify key stakeholders with regard to the linkage of VLEs, MLEs and digital libraries -To identify key stakeholder forum points and dissemination routes -To identify the relevant issues, according to the stakeholders and to previous research, pertaining to the interaction (both possible and potential) between VLEs/MLEs and digital libraries -To critically analyse identified issues, based on stakeholder experience and practice; output of previous and current projects; and prior and current research -To report back to JISC and to the stakeholder communities, with results situated firmly within the context of JISC's strategic aims and objectives

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Uganda: Data Strategy and Capacity Building

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    As part of Uganda's commitment to the Sustainable Development Agenda, the country has made substantial progress toward improved national development data—including the launch of a Development Data Hub supported by Development Initiatives and a review of open data readiness jointly undertaken by the government and the World Bank. Uganda however, lacks an organized framework for collecting and sharing reliable and comparable data on philanthropy. As such, the newly established Uganda National Philanthropy Forum (UPF) represents a key mechanism for the sector to consolidate its e orts and hone its contributions to national development. The forum was established in October 2015, facilitated by the East Africa Association of Grantmakers (EAAG), in partnership with Independent Development Fund (IDF), Development Network of Indigenous Voluntary Associations (DENIVA) and GoBig Hub. Its objective is to explore strategies for consolidating and organizing the philanthropy sector in Uganda.As a follow up to the UPF agenda on advancing philanthropy data in Uganda, EAAG and the Foundation Center in partnership with IDF and DENIVA hosted a Data Scoping Meeting on October 25th 2016. The objective of the meeting was to explore opportunities to strengthen data sharing and management to enhance the sector's coordination and in uence on national development policy. The meeting brought together 35 foundations, trusts and other local philanthropy organizations

    E-Science in the classroom - Towards viability

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    E-Science has the potential to transform school science by enabling learners, teachers and research scientists to engage together in authentic scientific enquiry, collaboration and learning. However, if we are to reap the benefits of this potential as part of everyday teaching and learning, we need to explicitly think about and support the work required to set up and run e-Science experiences within any particular educational context. In this paper, we present a framework for identifying and describing the resources, tools and services necessary to move e-Science into the classroom together with examples of these. This framework is derived from previous experiences conducting educational e-Science projects and systematic analysis of the categories of ‘hidden work’ needed to run these projects (Smith, Underwood, Fitzpatrick, & Luckin, forthcoming). The articulation of resources, tools and services based on these categories provides a starting point for more methodical design and deployment of future educational e- Science projects, reflection on which can also help further develop the framework. It also points to the technological infrastructure from which such tools and services could be built. As such it provides an agenda of work to develop both processes and technologies that would make it practical for teachers to deliver active, and collaborative e-Science learning experiences on a larger scale within and across schools. Routine school e- Science will only be possible if such support is specified, implemented and made available to teachers within their work contexts in an appropriate and usable form

    Data as a Service (DaaS) for sharing and processing of large data collections in the cloud

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    Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.Peer ReviewedPostprint (author's final draft
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