Workshop on Enterprise Big Data Semantic and Analytics Modeling - overview
Workshop on Enterprise Big Data Semantic and Analytics Modeling
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
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. Much like "web data" enterprise data also has volume, variety, velocity, and veracity challenges. 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.
Workshop papers can fall into any of the following categories involving exploiting of enterprise bid data and/or enterprise applications:
Solution and 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
Main Conference: IEEE Big Data 2014
• 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
Paper Submission Link
Your paper should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines
Although we accept submissions in the form of PDF, PS, and DOC/RTF files, you are strongly encouraged to generate a PDF version for your paper submission if your paper was prepared in Word. Your paper should not exceed 4 pages (double column).