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    2015.7.29 noiz Equipo GNOSS

    Nuevas especificaciones para CSV ON THE WEB. Candidate Recommendation stage. W3C

    CSV (Comma Separated Values) es un formato antiguo, pero muy usado, de intercambio y publicación de datos en formato tabular. En el Grupo de Trabajo CSV on the Web, del W3C, se le está proporcionando una nueva vida, convirtiéndolo en un estándar Web de publicación de datos, incluyendo la declaración de formatos.

    La propuesta de estándar consta de estos 4 documentos: 

    Estos documentos toman CSV como su caso de uso, pero podrían aplicarse a cualquier otro formato tabular de datos compartidos (por ejemplo, TSV, Tab Separated Values). Se espera terminar la especificación a finales de octubre de 2015.

    Especialmente interesante resulta, en el ámbito de la Web Semántica y Linked Data, la especificación para convertir las filas de una tabla en triples RDF, mediante el uso de plantillas. 


    En este video de 43´, Evan Sandhaus, responsable de la puesta en marcha del proyecto Linked Data en el New York Times explica cómo en el año 2009 el New York Times empezó a publicar sus datos utilizando los estándares de la Web semántica.

    Una de las explotaciones más interesantes en su explotación a través de la puesta en marcha de un buscador facetado para su fondo documental visible en www.nytexplorer.com . Es posible facetar por persona, localización, tema y columna del periódico.

    The New York Times committment to Linked Data began over 160 years ago. Starting in 1851, The New York Times has always catalogued its archival articles using a controlled vocabulary of people, places, organizations and descriptors. In 2009 The New York Times started publishing this vocabulary as linked data using semantic web standards.

    In 2011 The Times announced the launch of several RESTful Semantic APIs. And in late 2012 and early 2013, The Times will migrate its entire process for vocabulary management to a system designed around the principles of Linked Data. In my remarks, I will survey the history of Semantic publishing at The New York Times, outline our semantic strategy, detail the business-case for linked data at The Times and provide an in-depth explanation of our new vocabulary management system.


    Linked Data tools: Semantic Web for the masses

    Semantic Web technologies have immense potential to transform the Internet into a distributed reasoning machine that will not only execute extremely precise searches, but will also have the ability to analyze the data it finds to create new knowledge. This paper examines the state of Semantic Web (also known as Linked Data) tools and infrastructure to determine whether semantic technologies are sufficiently mature for non–expert use, and to identify some of the obstacles to global Linked Data implementation.


    Repositorio sobre actividad cultural en Italia

    En esta pagina es posible encontrar recursos sobres actividades culturales en link open data en Italia?

    L’uso degli standards del Semantic Web e l’adesione ai principi dei Linked Data offrono al mondo della conservazione del patrimonio culturale di rendere quelle risorse digitali “visibili e riusabili” nell’universo del Web, anche al di fuori dell’originale contesto di utilizzo.
    Questa evoluzione può far crescere la presenza di archivi e biblioteche sul Web, favorire l’emersione dei contenuti digitali di queste istituzioni e, in tal modo, dare supporto alla ricerca interdisciplinare.
    L’utilizzo di Library Linked Data offre una straordinaria possibilità di dare a queste risorse informative stabilità e persistenza indipendentemente dai formati e dai software utilizzati per la loro produzione, liberando, allo stesso tempo, le istituzioni culturali dalla “dipendenza” da un limitato numero di fornitori tecnologici specializzati.



    Gnoss Metalibrary Brochure

    tipo de documento Pdf

    GNOSS Meta-library is the solution to build a semantic library of libraries, aggregating works and metadata of multiple libraries and making them available as Linked Data.

    The basis underlying the Meta-library project is building a unified graph of library resources and authors in order that each node is represented by a single URI, so that the author is always the same one regardless of the library where the books are located. For example, Cervantes will be the same author of a book in the Spanish National Library or in the Miguel de Cervantes Virtual Library.

    As GNOSS Meta-library works according to the standards of the Semantic Web and the principles of the Linked Open Data Web, it can connect with other parts of the Linked Open Data Web, like DBpedia, Freebase or Geonames.

    GNOSS meta-library incorporates end-user oriented applications, like facet-based searches and semantic context creation, which drastically improve user experience.


    Welcome to LDBC | Linked Data Benchmark Council

    Welcome to LDBC

    In the last years we have seen an explosion of massive amounts of graph shaped data coming from a variery of applications that are related to social networks like facebook, twitter, blogs and other on-line media and telecommunication networks. Furthermore, the W3C linking open data initiative has boosted the publication and interlinkage of a large number of datasets on the semantic web resulting to the Linked Data Cloud. These datasets with billions of RDF triples such as Wikipedia, U.S. Census bureau, CIA World Factbook, DBPedia, and government sites have been created and published online. Moreover, numerous datasets and vocabularies from e-science are published nowadays as RDF graphs most notably in life and earth sciences, astronomy in order to facilitate community annota- tion and interlinkage of both scientific and scholarly data of interest.

    Technology and bandwidth now provide the opportunities for compiling, publishing and sharing massive Linked Data datasets. A significant number of commercial semantic repositories (RDF databases with reasoner and query-engine) which are the cornerstone of the Semantic Web exist.

    Neverthless at the present time,

    • there is no comprehensive suite of benchmarks that encourage the advancement of technology by providing both academia and industry with clear targets for performance and functionality and
    • no independent authority for developing benchmarks and verifying the results of those engines. The same holds for the emerging field of noSQL graph databases, which share with RDF a graph data model and pattern- and pathoriented query languages.

    The Linked Data Benchmark Council (LDBC) project aims to provide a solution to this problem by making insightful the critical properties of graph and RDF data management technology, and stimulating progress through compettion. This is timely and urgent since non-relational data management is emerging as a critical need for the new data economy based on large, distributed, heterogeneous, and complexly structured data sets. This new data management paradigm also provides an opportunity for research results to impact young innovative companies working on RDF and graph data management to start playing a significant role in this new data economy.


    The linked data value chain

    tipo de documento Pdf

    Linked Data is as essential for the Semantic Web as hypertext has been for the Web. For this reason, the W3C community project Linking Open Data has been facilitating the transformation of publicly available, open data into Linked Data since 2007. As of 2009, the vast majority of Linked Data is still generated by research communities and institutions. For a successful corporate uptake, we deem it important to have a strong conceptual groundwork, providing the foundation for the development
    of business cases revolving around the adoption of Linked Data. We therefore present the Linked Data Value Chain, a model that conceptualizes the current Linked Data sphere. The Linked Data Value Chain helps to identify and categorize potential pitfalls which have to be considered by business engineers. We demonstrate this process within a concrete case study involving the BBC.



    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 we present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. We 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.





    2012.9.2 noiz Equipo GNOSS

    Interesante informe publicado por Mathieu d’Aquin, experto en Web Semántica del Knowledge Media Institute (The Open University, UK) en junio de 2012 en el que analiza la utilización de los datos abiertos enlazados (Linked Data) en educación:

    "In this report, we introduce a recent development in the area of Web technologies which has the potential to revolutionise the area of ODL: The Semantic Web. While the Semantic Web has been, until now mostly considered from a research perspective, we focus here on the concrete benefit that can today be obtained from applying the set of principles and technologies that have emerged from the most pragmatic part of the Semantic Web field: Linked Data.

    In this report we describe how this idea is being realised and how it can be adopted by organisations willing to contribute, interlink to and take advantage of the Web of Linked Data for ODL. We describe the tools, technologies and processes to publish and use Linked Data in a concrete way, focusing in particular on learning and teaching applications. Understanding both the costs and benefits of adopting Linked Data and Semantic Web technologies is, of course, a critical part of the process. Alongside the description and explanation of the technological notions related to this area we show how such notions can be applied to solve some of the specific problems faced in ODL and present a number of case studies in which such benefits have been concretely achieved"


    Ensemble Project:  Semantic Technologies for the Enhancement of Case Based Learning


    The Ensemble Project

    “Ensemble: Semantic Technologies for the Enhancement of Case Based Learning” project is one of eight projects currently funded under the joint ESRC and EPSRC Technology Enhanced Learning Programme, which is part of the broader Teaching and Learning Research Programme (TLRP). This research and development project will commence work in October 2008 and will run for three years.

    The project has explored the potential of emerging Semantic Web and Linked Data technologies to support teaching in complex, controversial and rapidly-evolving fields where case based learning is the pedagogical approach of choice. This involved working with teachers and students in undergraduate and postgraduate courses to explore both the nature and role of the cases around which learning is focused, and the part that emerging Semantic Web technologies and approaches can play in supporting this learning.

    From the outset, it was recognised that teaching and learning environments are complex and evolving, and that participants in these environment may have multiple identities – as teachers, learners, researchers and workers. The learning technologies they use need to be robust yet flexible enough to support teachers and learners as they grapple with complex situations and develop creative solutions