42,716 research outputs found

    Linked Data - the story so far

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    The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

    A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

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    Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

    Supporting decision-making in the building life-cycle using linked building data

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    The interoperability challenge is a long-standing challenge in the domain of architecture, engineering and construction (AEC). Diverse approaches have already been presented for addressing this challenge. This article will look into the possibility of addressing the interoperability challenge in the building life-cycle with a linked data approach. An outline is given of how linked data technologies tend to be deployed, thereby working towards a “more holistic” perspective on the building, or towards a large-scale web of “linked building data”. From this overview, and the associated use case scenarios, we conclude that the interoperability challenge cannot be “solved” using linked data technologies, but that it can be addressed. In other words, information exchange and management can be improved, but a pragmatic usage of technologies is still required in practice. Finally, we give an initial outline of some anticipated use cases in the building life-cycle in which the usage of linked data technologies may generate advantages over existing technologies and methods

    Towards structured sharing of raw and derived neuroimaging data across existing resources

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    Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery

    XML content warehousing: Improving sociological studies of mailing lists and web data

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    In this paper, we present the guidelines for an XML-based approach for the sociological study of Web data such as the analysis of mailing lists or databases available online. The use of an XML warehouse is a flexible solution for storing and processing this kind of data. We propose an implemented solution and show possible applications with our case study of profiles of experts involved in W3C standard-setting activity. We illustrate the sociological use of semi-structured databases by presenting our XML Schema for mailing-list warehousing. An XML Schema allows many adjunctions or crossings of data sources, without modifying existing data sets, while allowing possible structural evolution. We also show that the existence of hidden data implies increased complexity for traditional SQL users. XML content warehousing allows altogether exhaustive warehousing and recursive queries through contents, with far less dependence on the initial storage. We finally present the possibility of exporting the data stored in the warehouse to commonly-used advanced software devoted to sociological analysis

    Mixing the reactive with the personal: Opportunities for end-user programming in personal information management

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    The transition of personal information management (PIM) tools off the desktop to the Web presents an opportunity to augment these tools with capabilities provided by the wealth of real-time information readily available. In this chapter, we describe a personal information assistance engine that lets end-users delegate to it various simple context- and activity-reactive tasks and reminders. Our system, Atomate, treats RSS/ATOM feeds from social networking and life-tracking sites as sensor streams, integrating information from such feeds into a simple unified RDF world model representing people, places and things and their time-varying states and activities. Combined with other information sources on the web, including the user's online calendar, web-based e-mail client, news feeds and messaging services, Atomate can be made to automatically carry out a variety of simple tasks for the user, ranging from context-aware filtering and messaging, to sharing and social coordination actions. Atomate's open architecture and world model easily accommodate new information sources and actions via the addition of feeds and web services. To make routine use of the system easy for non-programmers, Atomate provides a constrained-input natural language interface (CNLI) for behavior specification, and a direct-manipulation interface for inspecting and updating its world model

    Pathways: Augmenting interoperability across scholarly repositories

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    In the emerging eScience environment, repositories of papers, datasets, software, etc., should be the foundation of a global and natively-digital scholarly communications system. The current infrastructure falls far short of this goal. Cross-repository interoperability must be augmented to support the many workflows and value-chains involved in scholarly communication. This will not be achieved through the promotion of single repository architecture or content representation, but instead requires an interoperability framework to connect the many heterogeneous systems that will exist. We present a simple data model and service architecture that augments repository interoperability to enable scholarly value-chains to be implemented. We describe an experiment that demonstrates how the proposed infrastructure can be deployed to implement the workflow involved in the creation of an overlay journal over several different repository systems (Fedora, aDORe, DSpace and arXiv).Comment: 18 pages. Accepted for International Journal on Digital Libraries special issue on Digital Libraries and eScienc
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