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Featured Keynote Lecture - Prof. Amit Sheth

Last modified 2014-09-04 18:44

Smart Data for you and me: Personalized and Actionable Physical Cyber Social Big Data
Prof. Amit Sheth
Fellow, IEEE; LexisNexis Eminent Scholar
Founder/Executive Director, Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis)
Professor of Computer Science, Wright State University, Ohio, USA
Prof. Sheth is one of the highest cited researchers with about 28,000 citations to his published papers

Date & Time: 08:45am - 09:45am; July 21 (Monday), 2014
LOCATION: Monte Carlo (Blue Man Group) Theater


    Big Data has captured a lot of interest in industry, with the emphasis on the challenges of the four Vs of Big Data: Volume, Variety, Velocity, and Veracity, and their applications to drive value for businesses. Recently, there is rapid growth in situations where a big data challenge relates to making individually relevant decisions. A key example is human health, fitness, and well-being. Consider for instance, understanding the reasons for and avoiding an asthma attack based on Big Data in the form of personal health signals (e.g., physiological data measured by devices/sensors or Internet of Things around humans, on the humans, and inside/within the humans), public health signals (information coming from the healthcare system such as hospital admissions), and population health signals (such as Tweets by people related to asthma occurrences and allergens, Web services providing pollen and smog information, etc.). However, no individual has the ability to process all these data without the help of appropriate technology, and each human has different set of relevant data!

    In this talk, I will forward the concept of Smart Data that is realized by extracting value from Big Data, to benefit not just large companies but each individual. If I am an asthma patient, for all the data relevant to me with the four V-challenges, what I care about is simply, “How is my current health, and what is the risk of having an asthma attack in my personal situation, especially if that risk has changed?” As I will show, Smart Data that gives such personalized and actionable information will need to utilize metadata, use domain specific knowledge, employ semantics and intelligent processing, and go beyond traditional reliance on ML and NLP.

    For harnessing volume, I will discuss the concept of Semantic Perception, that is, how to convert massive amounts of data into information, meaning, and insight useful for human decision-making. For dealing with Variety, I will discuss experience in using agreement represented in the form of ontologies, domain models, or vocabularies, to support semantic interoperability and integration. For Velocity, I will discuss somewhat more recent work on Continuous Semantics, which seeks to use dynamically created models of new objects, concepts, and relationships, using them to better understand new cues in the data that capture rapidly evolving events and situations.

    Smart Data applications in development at Kno.e.sis come from the domains of personalized health, energy, disaster response, and smart city. I will present examples from a couple of these.


    Prof. Amit Sheth ( is an educator, researcher, and entrepreneur. He is the LexisNexis Eminent Scholar and founder/executive director of the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) at Wright State University. Kno.e.sis conducts research in social/sensor/semantic data and Web 3.0 with real-world applications and multidisciplinary solutions for translational research, healthcare and life sciences, cognitive science, material sciences, and others. Kno.e.sis' activities have resulted in Wright State University being recognized as a top organization in the world on World Wide Web in research impact. Prof. Sheth is one of top authors in Computer Science, World Wide Web, and databases (cf: Microsoft Academic Search; Google H-index=85). His research has led to several commercial products, many real-world applications, and two earlier companies with two more in early stages of development. One of these was Taalee/Voquette/Semagix, which was likely the first company (founded in 1999) that developed Semantic Web enabled search and analysis, and semantic application development platforms.
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