15,371 research outputs found

    Development of Use Cases, Part I

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    For determining requirements and constructs appropriate for a Web query language, or in fact any language, use cases are of essence. The W3C has published two sets of use cases for XML and RDF query languages. In this article, solutions for these use cases are presented using Xcerpt. a novel Web and Semantic Web query language that combines access to standard Web data such as XML documents with access to Semantic Web metadata such as RDF resource descriptions with reasoning abilities and rules familiar from logicprogramming. To the best knowledge of the authors, this is the first in depth study of how to solve use cases for accessing XML and RDF in a single language: Integrated access to data and metadata has been recognized by industry and academia as one of the key challenges in data processing for the next decade. This article is a contribution towards addressing this challenge by demonstrating along practical and recognized use cases the usefulness of reasoning abilities, rules, and semistructured query languages for accessing both data (XML) and metadata (RDF)

    Generating Natural Language from Linked Data:Unsupervised template extraction

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    We propose an architecture for generating natural language from Linked Data that automatically learns sentence templates and statistical document planning from parallel RDF datasets and text. We have built a proof-of-concept system (LOD-DEF) trained on un-annotated text from the Simple English Wikipedia and RDF triples from DBpedia, focusing exclusively on factual, non-temporal information. The goal of the system is to generate short descriptions, equivalent to Wikipedia stubs, of entities found in Linked Datasets. We have evaluated the LOD-DEF system against a simple generate-from-triples baseline and human-generated output. In evaluation by humans, LOD-DEF significantly outperforms the baseline on two of three measures: non-redundancy and structure and coherence.

    From RESTful Services to RDF: Connecting the Web and the Semantic Web

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    RESTful services on the Web expose information through retrievable resource representations that represent self-describing descriptions of resources, and through the way how these resources are interlinked through the hyperlinks that can be found in those representations. This basic design of RESTful services means that for extracting the most useful information from a service, it is necessary to understand a service's representations, which means both the semantics in terms of describing a resource, and also its semantics in terms of describing its linkage with other resources. Based on the Resource Linking Language (ReLL), this paper describes a framework for how RESTful services can be described, and how these descriptions can then be used to harvest information from these services. Building on this framework, a layered model of RESTful service semantics allows to represent a service's information in RDF/OWL. Because REST is based on the linkage between resources, the same model can be used for aggregating and interlinking multiple services for extracting RDF data from sets of RESTful services

    Including widespread geometry formats in semantic graphs using RDF literals

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    The exchange of building data involves both geometric and non-geometric data. A promising Linked Data approach is to embed data from existing geometry formats inside Resource Description Framework (RDF) literals. Based on a study of relevant specifications and related work, this toolset-independent approach was found suitable for the exchange of geometric construction data. To implement the approach in practice, the File Ontology for Geometry formats (FOG) and accompanying modelling method is developed. In a proof-of-concept web application that uses FOG, is demonstrated how geometry descriptions of different existing formats are automatically recognised and parsed

    Relating geometry descriptions to its derivatives on the web

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    Sharing building information over the Web is becoming more popular, leading to advances in describing building models in a Semantic Web context. However, those descriptions lack unified approaches for linking geometry descriptions to building elements, derived properties and derived other geometry descriptions. To bridge this gap, we analyse the basic characteristics of geometric dependencies and propose the Ontology for Managing Geometry (OMG) based on this analysis. In this paper, we present our results and show how the OMG provides means to link geometric and non-geometric data in meaningful ways. Thus, exchanging building data, including geometry, on the Web becomes more efficient

    Linked education: interlinking educational resources and the web of data

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    Research on interoperability of technology-enhanced learning (TEL) repositories throughout the last decade has led to a fragmented landscape of competing approaches, such as metadata schemas and interface mechanisms. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de-facto standard for sharing data on the Web and offers a large potential to solve interoperability issues in the field of TEL. In this paper, we describe a general approach to exploit the wealth of already existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain. This approach has been implemented in the context of the mEducator project where data from a number of open TEL data repositories has been integrated, exposed and enriched by following Linked Data principles
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