Title

Semantics-Empowered Approaches to Big Data Processing for Physical-Cyber-Social Applications

Document Type

Report

Publication Date

11-2013

Abstract

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the five V’s of Big Data, where four of the Vs are harnessed to produce the fifth V- value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing can be done at a level independent of heterogeneity of data formats and media. To handle the challenge of Velocity, we seek to use continuous semantics capability to dynamically create event or situation specific models and recognize new concepts, entities and facts. To handle Veracity, we explore the formalization of trust models and approaches to glean trustworthiness. The above four Vs of Big Data are harnessed by the semantics-empowered analytics to derive Value for supporting practical applications transcending physical-cyber-social continuum.

Comments

Presented at the AAAI Fall Symposium Series, Arlington, VA, November 15-17, 2013.

A presentation that accompanied the report is available at http://www.slideshare.net/knoesis/semantics-forbigdataprocessing.


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