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Semantic web for the Working Ontologist: Effective Modeling for Linked Data, Rdfs, and owl (Acm Books) (en Inglés)
James Hendler; Fabien Gandon; Dean Allemang (Autor)
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Acm Books
· Tapa Blanda
Semantic web for the Working Ontologist: Effective Modeling for Linked Data, Rdfs, and owl (Acm Books) (en Inglés) - James Hendler; Fabien Gandon; Dean Allemang
$ 344.247
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Origen: Estados Unidos
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Reseña del libro "Semantic web for the Working Ontologist: Effective Modeling for Linked Data, Rdfs, and owl (Acm Books) (en Inglés)"
Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today. The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way. The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.
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