325,279 research outputs found

    Applying Semantic Web Technologies to Medieval Manuscript Research

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    Medieval manuscript research is a complex, fragmented, multilingual field of knowledge, which is difficult to navigate, analyse and exploit. Though printed sources are still of great importance and value to researchers, there are now many services on the Web, some commercial and many in the public domain. At present, these services have to be consulted separately and individually. They employ a range of different descriptive standards and vocabularies, and use a variety of technologies to make their information available on the Web. This chapter proposes a new approach to organizing the international collaborative infrastructure for interlinking knowledge and research about medieval European manuscripts, based on technologies associated with the Semantic Web and the Linked Data movement. This collaborative infrastructure will be an open space on the Web where information about medieval manuscripts can be shared, stored, exchanged and updated for research purposes. It will be possible to ask large-scale research questions across the virtual global manuscript collection, in a quicker and more effective way than has ever been feasible in the past. The proposed infrastructure will focus on building links between data and will provide the basis for new kinds of services which exploit these data. It will not aim to impose a single metadata standard on existing manuscript services, but will build on existing databases and vocabularies. The article describes the architecture, services and data which will comprise this infrastructure, and discusses strategies for making th challenging and exciting goal a reality

    Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases

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    Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org

    Map4rdf - Faceted Browser for Geospatial Datasets

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    Recently we have seen a large increase in the amount of geospatial data that is being published using RDF and Linked Data principles. Eorts such as the W3C Geo XG, and most recently the GeoSPARQL initiative are providing the necessary vocabularies to pub- lish this kind of information on the Web of Data. In this context it is necessary to develop applications that consume and take advantage of these geospatial datasets. In this paper we present map4rdf, a faceted browsing tool for exploring and visualizing RDF datasets enhanced with geospatial information

    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

    Hypermedia-based discovery for source selection using low-cost linked data interfaces

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    Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness
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