Variety, Velocity, Volume and Veracity are the four Vs for Big Data. Most of the technologies available have shown how to treat the Volume. However, due to the increasing number of streaming data sources, the Velocity problem is as relevant as never before. Moreover, Veracity and especially Variety problems have increased the difficulty of the challenge.

Recently, a 3 day mini-course/tutorial was offed at the Ohio Center of Excellence in Knowledge-enabled computing (Kno.e.sis) at Wright State University. The focus was on two aspects of the Big Data problem- Velocity and Variety. In particular, we discussed how with streaming data and semantic technologies it is possible to enable efficient and effective stream processing for advanced application development. The speakers were Dr. Emanuele Della Vella and Riccardo Tommasini from Politecnico di Milano, and Prof. Amit Sheth, Pramod Anantharam and Pavan Kapanipathi from Kno.e.sis.

Covered Topics

• Big Data Introduction with focus on textual and sensor streaming data
• Deep into Velocity:
  • History and principles of stream computing and complex event processing
  • Modelling frameworks for complex event processing and data stream management
  • Processing social data streams
  • Physical (sensor/IoT)
• Deep into Variety:Variety and Velocity at once: Stream reasoning, Tools and applicationsVariety and Velocity at once: Stream reasoning, Tools and applications
  • Semantic Web standards, languages, models, query processing, and reasoning techniques relevant to various modalities and integrated processing.

Provision

Attendees will gain enough background to use tools made available by the academic and industrial community to solve prototypical problems. Example applications include: Smart Cities, Social Media Analytics, Sensor Networks, Situational Awareness, Digital Health, etc.

Suggested Pre-Requisite Knowledge

Intermediate IT level (programming or application development skills, knowledge of data management and Web technologies).

All content from the course (slides, video) are on-line at: http://wiki.knoesis.org/index.php/BigDataTutorial 

Citation:

E. Della Vella, A. Sheth, R. Tommasini, P. Anantharam, P. Kapanipathi: "Semantic Approach to Big Data and Event Processing," Short Course at Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis), Wright State University, Dayton, USA. Oct 6-8, 2015. 

(c) Speakers, Politecnico di Milano and Wright State University. Content is made  available for individual educational use only (rehosting, broadcasting and any commercial use is prohibited).