IEEE BigData 2014 Workshop on Enterprise Big Data Semantics and Analytics Modeling

The workshop on Enterprise Big Data Semantics and Analytics Modeling is co-located at the IEEE BigData 2014 conference in Oct 27-30, Washington DC, USA.

Call for Papers

Objectives

While big data has been a topic of research and industry activity, much of it has been focused on unstructured data such as web logs, web crawl data, and social media data. One area which has received less attention but offers significant opportunities is that of “enterprise big data”. As enterprises drive towards leveraging analytics to create new value, they are faced with one of the most daunting challenges post the enterprise data warehousing era, “How can we link data from 100’s of business processes, tens of businesses, and combine relevant enterprise data with external data to enable novel analytical insights?” Consequently, Enterprise Big Data Semantics, Analytics and Modeling (EBDSAM) is an emerging area of research. It involves developing a new paradigm and technologies for handling of enterprise data which also face volume, variety, velocity, and veracity to create value through contextual process and analytics to create novel insights and enable improved decisions.

This workshop will bring together academic researchers, technology company researchers, and industry practitioners from multiple industries, including Retail, Banking, Travel and Transportation, Government, etc. The goal of the workshop will be to share key challenges in EBDSAM, novel approaches to solutions, key business challenges that can be addressed by EBDSAM. Participants are encouraged to start with specific business scenarios and demonstrate research prototypes they have created in the EBDSAM area.

Topics of Interest

Workshop papers can fall into any of the following categories involving exploiting of enterprise bid data and/or enterprise applications:

• Solution / applications and industry scenarios for EBDSAM
• Semantic Domain Models and Ontologies
• Dynamic and configurable data linking and data extractors mechanisms
• Analytics driven auto generated data models / linkers
• Automatic linking discovery technologies
• Architecture for EBDSAM leveraging, Hadoop, Cassandra, MongoDB, etc…
• Cloud based Scaling of EBDSAM systems.
• Additional related categories not covered above

Important Dates

• Aug 10, 2014: Due date for full workshop papers submission

• Sept 20, 2014: Notification of paper acceptance to authors 

• Oct 5, 2014: Camera-ready of accepted papers 

• October 27-30 2014: Workshops

Workshop Organizers

Arun Hampapur, Director and Distinguished Engineer, IBM Watson Research, Smarter Commerce and Supply Chain

Amit Sheth Kno.e.sis - Ohio Center of Excellence in Knowledge-enabled Computing, LexisNexis Ohio Eminent Scholar, Wright State University