173 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

    An Approach to Publish Spatial Data on the Web: The GeoLinked Data Case

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    In this paper we report on an ongoing process aimed at publishing hydrographical data on the Web with a Spanish GeoLinked Data Use Case. Moreover, we discuss the process we followed, and propose methodological guidelines for all the activities involved within the process

    Integration of linked open data in case-based reasoning systems

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    This paper discusses the opportunities of integrating Linked Open Data (LOD) resources into Case-Based Reasoning (CBR) systems. Upon the application domain travel medicine, we will exemplify how LOD can be used to fill three out of four knowledge containers a CBR system is based on. The paper also presents the applied techniques for the realization and demonstrates the performance gain of knowledge acquisition by the use of LOD

    ‚Linked Data‘ - und warum wir uns im hbz-Verbund damit beschäftigen

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    The topic “Linked Open Data“ is pushing more and more into the library sphere. While “Open Data“ is all about the legal status of any kind of data, “Linked Data“ aims at augmenting the interoperability of data by consistently applying (web-)standards. This article begins with an illustration of why “Linked Data“ is relevant to the library world. This is followed by a short introduction to the most important Linked Data standards and some thoughts on how to migrate bibliographic data to these standards. Finally the current activities of the hbz library network concerning this matter are presented

    A Linked Data Approach to Sharing Workflows and Workflow Results

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    A bioinformatics analysis pipeline is often highly elaborate, due to the inherent complexity of biological systems and the variety and size of datasets. A digital equivalent of the ‘Materials and Methods’ section in wet laboratory publications would be highly beneficial to bioinformatics, for evaluating evidence and examining data across related experiments, while introducing the potential to find associated resources and integrate them as data and services. We present initial steps towards preserving bioinformatics ‘materials and methods’ by exploiting the workflow paradigm for capturing the design of a data analysis pipeline, and RDF to link the workflow, its component services, run-time provenance, and a personalized biological interpretation of the results. An example shows the reproduction of the unique graph of an analysis procedure, its results, provenance, and personal interpretation of a text mining experiment. It links data from Taverna, myExperiment.org, BioCatalogue.org, and ConceptWiki.org. The approach is relatively ‘light-weight’ and unobtrusive to bioinformatics users

    Geographical Linked Data: a Spanish Use Case

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    We present the process that has been followed for the development of an application that makes use of several heterogeneous Spanish public datasets that are related to administrative, hydrographic, and statistical domains. Our application aims at analysing existing relations between the Spanish coastal area and dierent statistical variables such as unemployment, population, dwelling, industry, and building trade. Moreover, we provide an important innovation with respect to other similar processes followed in other initiatives by dealing with the geometrical information of features

    Preliminary results in tag disambiguation using DBpedia

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    The availability of tag-based user-generated content for a variety of Web resources (music, photos, videos, text, etc.) has largely increased in the last years. Users can assign tags freely and then use them to share and retrieve information. However, tag-based sharing and retrieval is not optimal due to the fact that tags are plain text labels without an explicit or formal meaning, and hence polysemy and synonymy should be dealt with appropriately. To ameliorate these problems, we propose a context-based tag disambiguation algorithm that selects the meaning of a tag among a set of candidate DBpedia entries, using a common information retrieval similarity measure. The most similar DBpedia en-try is selected as the one representing the meaning of the tag. We describe and analyze some preliminary results, and discuss about current challenges in this area
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