Semantics-Empowered Big Data Processing with Applications

To handle volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision making. To handle variety, we resort to semantic models and annotations of data so that intelligent processing can be done independent of heterogeneity of data formats and media. To handle velocity, we seek to use continuous semantics capability to dynamically create event-or situation-specific models and recognize relevant new concepts, entities and facts. To handle veracity, we explore trust models and approaches to glean trustworthiness. These four of the five v's of big data are harnessed by the semantics-empowered analytics to derive value to support applications transcending the physicalcyber-social continuum.