Inhaltsangabe
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 worldwide distributed web of knowledge in a meaningful way.
The third edition builds on this foundation to bring Semantic Web practice to the 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.
Über die Autorin bzw. den Autor
James Hendler is the Director of the Institute for Data Exploration and Applications and the Tetherless World Professor of Computer, Web and Cognitive Sciences at Rensselaer Polytechnic Institute (New York, NY, USA). He also is the director of the RPI-IBM Artificial Intelligence Research Collaboration and serves as a member of the board of the UK's charitable Web Science Trust and the advisory board of timbr.ai. James has authored over 400 books, technical papers, and articles. He is a former member of the US Air Force Science Advisory Board, and is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the British Computer Society (BCS), the Institute of Electrical and Electronics Engineers (IEEE), the American Association for the Advancement of Science (AAAS) and the Association for Computing Machinery (ACM) technical societies. He is also the former Chief Scientist of the Information Systems Office at the US Defense Advanced Research Projects Agency (DARPA) where he created the DARPA Agent Markup Program(DAML) which helped to fund the science and creation of the SemanticWeb. James was the first computer scientist to serve on the board of reviewing editors for Science, is the former editor-in-chief of IEEE Intelligent Systems, and is currently coeditor of the Data Intelligence journal jointly published by Massachusetts Institute of Technology (MIT) Press and the Chinese Academy of Science. In 2010, he was named one of the 20 most innovative professors in America by Playboymagazine and was selected as an "Internet Web Expert" by the US government. In 2016, became a member of the National Academies Board on Research Data and Information and in 2018 was elected a Fellow of the US National Academy of Public Administration.
Fabien Gandon is a Research Director and Senior Researcher at Inria, France. Fabien's PhD in 2002 pioneered the joint use of distributed artificial intelligence (AI) and the Semantic Web to manage a variety of data sources and users above a Web architecture. Then, as a research project leader at Carnegie Mellon University (Pittsburgh, PA, USA), he proposed AI methods to enforce privacy preferences in querying and reasoning about personal data. In 2004, having been recruited as a researcher at Inria, he began to study models and algorithms to integrate social media and knowledge-based AI systems on the Web while keeping humans in the loop. In 2012 Fabien became the representative of Inria atW3C and founded Wimmics, a joint research team working on bridging social and formal semantics on the Web with AI methods. In 2017 he established and became the Director of the Joint Research Laboratory between Inria the Qwant search engine. The same year he also became responsible for the research convention between the Ministry of Culture and Inria with a special interest for cultural data and applications. In 2018 Fabien became Vice Head of Science for the research center of Inria Sophia Antipolis – Méditerranée. Over the years and since 2002, Fabien also never stopped teaching Semantic Web and Linked Data, and he has authored several Massive Open Online Courses (MOOCs) on the topic.
Dean Allemang is a consultant specializing in Semantic Web deployments in a number of industries, including finance, media, government and pharmaceuticals. He works as a staff ontologist for the Enterprise Data Management (EDM) Council, working primarily on the Finance Industry Business Ontology (FIBO). He is a member of the advisory board of data.world, and formerly Chief Scientist at TopQuadrant, the first company in theUS devoted to the SemanticWeb. He was the recipient of a National Science Foundation Graduate Fellowship and the President's 300th Commencement Award at Ohio State University. He has studied and worked extensively throughout Europe and Australia, as a Marshall Scholar at Trinity College, Cambridge, UK from1982 through to 1984, was twice winner of the Swiss Technology Prize (1992 and 1996), and served as Chief Scientist of Capsicum Pty Ltd, an early adopter of Semantic Web Technology in Australia. He has served as an invited expert on numerous international review boards, including a review of the Digital Enterprise Research Institute – the world's largest Semantic Web research institute, and the Innovative Medicines Initiative, a collaboration between a consortium of pharmaceutical companies and the European Commission to set the roadmap for information management in the pharmaceutical industry for the near future.
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