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    Publicado el 18.12.2014 por Pablo Hermoso de Mendoza González

    Texto escrito por: Rafael Berlanga, Oscar Romero, Alkis Simitsis, Victoria Nebot, Torben Bach Pedersen,Alberto Abelló. María José Aramburu.

    Los autores hacen un análisis de cómo las tecnologías asociadas a la Web Semántica están impactando en el ámbito de la inteligencia de negocio, en los productos denominados Business Intelligence.

    Resumen su artículo de esta forma:

    His chapter describes the convergence of two of the most influential technologies in the last decade, namely business intelligence (BI) and the Semantic Web (SW). Business intelligence is used by almost any enterprise to derive important business-critical knowledge from both internal and (increasingly) external data. When using external data, most often found on the Web, the most important issue is knowing the precise semantics of the data. Without this, the results cannot be trusted. Here, Semantic Web technologies come to the rescue, as they allow semantics ranging from very simple to very complex to be specified for any web-available resource. SW technologies do not only support capturing the “passive” semantics, but also support active inference and reasoning on the data. The chapter first presents a motivating running example, followed by an introduction to the relevant SW foundation concepts. The chapter then goes on to survey the use of SW technologies for data integration, including semantic

     

     

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    Publicado el 18.3.2013 por Pablo Hermoso de Mendoza González

    How can Europe take the lead in the business of data?

    There are many reasons that explain why data is becoming increasingly important in our lives.

    --- Posted by Khalil Rouhana , DG INFSO, Director "Digital Content and Cognitive Systems"

    There are many reasons that explain why data is becoming increasingly important in our lives.

    Firstly, a large number of devices - from scientific instruments like genomic sequencers or telescopes to mobile phones to very tiny sensors -  generate much more data than humans could by themselves.

    Secondly, advances in digital storage technologies mean it is now cost effective to store large quantities of data for further analysis.

    Finally, advances in information retrieval to data mining and machine learning have made it possible to extract very valuable information from enormous amounts of data so that we are now able to analyse phenomena that were too big for us to perceive.

    Size is not the only thing that has changed. In the last few years we have discovered that certain types of data  -particularly non-private data collected by public administrations- are worth more when shared than when locked up. And that datasets are worth even more when they are linked to one another so that properties of various objects of interest -companies, products, and geographic features- can be aggregated from independently developed datasets.

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    Publicado el 8.1.2013 por Equipo GNOSS

    13 Semantic Markup Tips For 2013: A Local SEO Checklist (searchengineland.com)

    Serie de recomendaciones SEO basadas en tecnología semántica:

    "One of the least-tapped areas of local business website optimization continues to be semantic markup. Semantic markup can increase chances that information from your website will be highlighted in search engine results pages via rich snippets, attracting greater attention and clickthroughs".

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    Publicado el 17.12.2012 por Pablo Hermoso de Mendoza González

    En esta presentación es posible ver cual es la previsión y evolución de la web semántica en la primera década del siglo XXI según la visión de Mills Davis.

    Mills Davis is TopQuadrant’s managing director for industry research and strategic programs. He consults with technology manufacturers, global 2000 corporations, and government agencies on next-wave semantic
    technologies and solutions. Mills serves as lead for the Federal CIO Council’s Semantic Interoperability Community of Practice (SICoP) research into the business value of semantic technologies (Module-2).
     

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    Publicado el 22.10.2012 por Equipo GNOSS

    Two paradoxes at the heart of MOOCs (Learning Innovation)

    Nuevos argumentos para el debate en torno al fenómeno MOOC: "My thinking on MOOCs has been consolidated after doing a fair bit of reading, chatting and thinking recently.  Much has been written on the disruptive potential of MOOCs and also about the problems associated with them such as lack of quality, plagiarism and lack of tutor support.   I have no desire to add to the noise and hype but want to set down two paradoxes that it seems to me are at the heart of the MOOC movement

    Paradox 1:  Most MOOCs are offered by elite institutions which don’t need to expand their student base

    Paradox 2: Highly successful MOOCs attack the core business of those who are offering them"

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    Publicado el 13.8.2012 por Equipo GNOSS

    Semantic: Technology & Business UK

    El evento Semantic: Technology & Business tendrá lugar en Londres entre los días 19 y 20 de Septiembre de 2012. En el se presentarán algunas de las aplicaciones más atractivas de la Web semántica hoy en día en la industria y el comercio. Entre los temas de interes incluye:

    • Semantica para ciudades inteligentes for Smarter Cities
    • Semantica para educación
    • Semantica para la gestión de contenidos
    • Semantica para grandes empresas

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    Publicado el 3.1.2012 por Ricardo Alonso Maturana

    Wal-Mart: The Next Data Company? (Semantic Web)

    Joe McKendrick recently reported on Wal-Mart’s growing influence, not as a retailer, but as a data business. McKendrick writes, “Already, the lines have blurred between traditionally non-information technology companies and IT companies to the point where you can’t tell the two apart. But what’s really of value is not the software that’s being produced and shared, it’s the data that’s being generated and analyzed. This represents the future of many businesses — again, traditionally non-IT businesses — as they seek competitive advantage in a hyper-competitive global marketplace.” continued…New Career Opportunities Daily: The best jobs in media.

    Publicado en semanticweb.com el: 1/3/2012 12:40:01 PM

    Puedes ver los comentarios originales aqui

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    Publicado el 3.1.2012 por Ricardo Alonso Maturana

    How to Characterize Quality for Data Products (Semantic Web)

    Stephan Zednik has been working on the problem of accurately characterizing quality for science data products. He writes, “Science product quality is hard to define, characterize, and act upon. Product quality reflects a comparison against standard products of a similar kind, but it is also reflective of the fitness-for-use of the product for the end-user. Users weigh quality characteristics (e.g. accuracy, completeness, coverage, consistency, representativeness) based on their intended use for the data, and therefore quality of a product can be different based on different users’ needs and interests.  Despite the subjective nature of quality assertions, and their sensitivity to users fitness-for-use, most quality information is provided by the product producer and the subjective criteria used to determine quality is opaque, if available at all.” continued…New Career Opportunities Daily: The best jobs in media.

    Publicado en semanticweb.com el: 1/3/2012 2:00:28 PM

    Puedes ver los comentarios originales aqui

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    Publicado el 2.11.2011 por Equipo GNOSS

    'Could data save newspapers?' (Inma - Kylie Davis)

    Interesante artículo en el que se analiza la repercusión que pueden tener las estrategias basadas en datos en medios de comunicación:

    McKinsey offers up five areas to consider:

     

    1. Data is no longer proprietary. Rather, it is undergoing “radical transparency.” Consider the implications for your business.

    2. Big data allows you test all your decisions and conduct experiments. Consider how that could change the way you compete.

    3. Big data allows widespread, real-time customisation. Could this be a game changer in your business? The answer for newspapers is clearly ‘yes’ on this. We’re seeing the impact of it already.

    4. Big data can augment or even replace management, or some managerial decisions. (Bring it!)

      1. New business models are being built on data.

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    Compartido el 29.9.2011 por Equipo GNOSS

    Four data trends to rule them all, the data scientist king to bind them (Scraper Data Wiki Blog)

    Francis Irving lanza cuatro tendencias en datos:

    1. Super Moore’s law for data

    2. Business of big data

    3. Collaboration of data

    4. The data scientist is king

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