Keynote Seminar delivered at IFIP TC12 AI Summer School, Kuala Lumpur, Malaysia 5-6 August 2014
Prof. (Em.) Dr Robert Meersman
Austria
Semantics, or the meaning of things –in particular of communicated and stored information, of course is a very old field of study, originally the near-exclusive playground of philosophers and logicians. Naturally these formal first principles still apply however to any intendedly meaningful information that is communicated with the help computers and stored in them, specifically inside information systems in the broadest possible interpretation of that term: it includes everything from files, websites, databases, networks, or indeed the internet itself.
Cloud Computing and Big Data Analytics
Cloud computing offers an exciting opportunity to bring on-demand applications to customers and is being used for delivering hosted services over the Internet and/or processing massive amount of data for business intelligence. In this talk, we will discuss the architecture of cloud computing, MapReduce, and Hadoop. We will then discuss how the cloud infrastructure and services can be used for big data analytics. Finally, we will discuss various big data applications such as social media analytics, fraud analytics, voice-of-customer analytics, etc.
Decision Making from Big Data Sets & Streams
There is little doubt that the digital infrastructure of the next decade will look radically different from today’s. All sorts of products and devices will be connected to the Internet and to each other via ultra-wide band 4G (and, soon, 5G) mobile networks. Massive streams of data from digital devices will go global, along with other types of social media and rich business data. According to many, the possibility of "going full data" (i.e. handling the entire event/data streams generated by people and organizations' behavior, as opposed to sampling them to obtain traditional datasets) has the potential to dramatically improve the quality of decision making, creating a wealth of business opportunities. However, the "full data" option is not straightforward. The talk will cover some important aspects of it. First, it will provide a clear understanding of when full data is better than sampling. Secondly, it will present techniques to perform the "semantic lifting" needed to bring events' (and context) representation at the level of abstraction suitable for specific decision making goals. Thirdly, the talk will review available architectural choices and component toolkits for data processing, as well as data integration, interoperability and trustworthiness standards.
5th – 6th August 2014, MIMOS, Kuala Lumpur, Malaysia
http://ifip-tc12.digital-ecology.org/
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