Viktor Mayer-Schönberger

Viktor Mayer-SchönbergerShort Bio:
Viktor Mayer-Schönberger is Professor of Internet Governance and Regulation at the Oxford Internet Institute / Oxford University. He is also a faculty affiliate of the Belfer Center of Science and International Affairs at Harvard University. In addition to the international bestseller "Big Data" (with Kenneth Cukier), Mayer-Schönberger has published ten books (including the awards-winning "Delete: The Virtue of Forgetting in the Digital Age" with Princeton University Press) and is the author of over a hundred articles and book chapters on the information economy. He was voted Top-5 Software Entrepreneur in Austria in 1991 and Person of the Year for the State of Salzburg in 2000. He has chaired the Rueschlikon Conference on Information Policy in the New Economy, bringing together leading strategists and decision-makers of the new economy. He is a frequent public speaker, and sought expert for print and broadcast media worldwide. He and his work have been featured in (among others) New York Times, Wall Street Journal, Financial Times, The Economist, Nature, Science, NPR, BBC, The Guardian, Le Monde, El Pais, Die Zeit, Der Spiegel, WIRED, Ars Technica, and Daily Kos. He is also on the boards of foundations, think tanks and organizations focused on studying the information economy, and advises governments, businesses and NGOs on new economy and information society issues.

Website: http://www.vmsweb.net/

Why Big Data Matters - a lot

Much has been made of "big data", our ability to gain novel insights from a comprehensive set of data points, but a lot of it is hype, and marketing-speak to sell more tools and consulting. In this talk, I will explain what Big Data really is, why it isn¹t just a marketing fad or the tool du jour, but a new way of making sense of the world around us, and consequently why Big Data matters a great deal, in particular also in the context of semantic technologies. But I will also mention why we need to be cautious and well aware of Big Data limitations when utilizing it.