BDCAT 2017

BDCAT 2017
BDCAT 2017 : The 4th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
Dates	2017/12/05T12:00:00 (iCal) - 2017/12/08T12:00:00
Homepage:	http://dsr.encs.vancouver.wsu.edu/BDCAT2017/
Location
Location:	Austin, United States
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Important dates
Submissions:	2017/08/15T12:00:00
Table of Contents

The 4th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2017) aims to provide a platform for researchers from both academia and industry to present new discoveries in the broad area of big data computing and applications. The first 3 events were held in London (BDC 2014), Cyprus (BDC 2015), and Shanghai (BDCAT 2016).

DATES AND LOCATION

BDCAT 2017 will be held in conjunction with the 10th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2017) in Austin, Texas, USA, December 5-8 2017.

TOPICS OF INTEREST

Topics of interest include, but are not limited to:

1. Big Data Science - Big Data Analytics - Data Science Models and Approaches - Algorithms for Big Data - Big Data Search and Information Retrieval Techniques - Data Mining and Knowledge Discovery Approaches - Machine Learning Techniques for Big Data - Big Data Acquisition, Integration, Cleaning, and Best Practices

2. Big Data Infrastructures and Platforms - Scalable Computing Models, Theories, and Algorithms - In-Memory Systems and Platforms for Big Data Analytics - Cyber-Infrastructure for Big Data - Performance Evaluation Reports for Big Data Systems - Storage Systems (including file systems, NoSQL, and RDBMS) - Resource Management Approaches for Big Data Systems - Many-Core Computing and Accelerators

3. Big Data Applications - Big Data Applications for Internet of Things - Mobile Applications of Big Data - Big Data Applications for Smart City - Healthcare Applications such as Genome Processing and Analytics - Scientific Application Case Studies on Cloud Infrastructure - Big Data in Social Networks - Data Streaming Applications

4. Big Data Trends and Challenges - Fault Tolerance and Reliability - Scalability of Big Data Systems - Energy-Efficient Algorithms - Big Data Privacy and Security - Big Data Archival and Preservation

5. Visualization of Big Data - Visual Analytics Algorithms and Foundations - Graph and Context Models for Visualization - Analytics Reasoning and Sense-making on Big Data - Visual Representation and Interaction - Big Data Transformation, and Presentation

IMPORTANT DATES

- Paper Submission Due: August 15, 2017 - Author Notification: September 15, 2017 - Camera Ready Papers Due: September 30, 2017 - Early Registration Deadline: September 30, 2017 - Conference: December 5 -December 8, 2017

PAPER SUBMISSION

Authors are invited to submit papers electronically. Submitted manuscripts should be structured as technical papers and may not exceed 10 letter size (8.5 x 11) pages including figures, tables and references using the following templates (IEEECS_confs_LaTeX, PDF, DOC). Authors should submit the manuscript in PDF format and make sure that the file will print on a printer that uses letter size (8.5 x 11) paper. The official language of the meeting is English. All manuscripts will be reviewed and will be judged on correctness, originality, technical strength, significance, quality of presentation, and interest and relevance to the conference attendees. Papers conforming to the above guidelines can be submitted through the BDCAT 2017 paper submission system (https://easychair.org/conferences/?conf=bdcat2017)

Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review. Submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. Authors may contact the conference PC Chair for more information.

CALL FOR PAPERS

Call for papers available here: http://dsr.encs.vancouver.wsu.edu/BDCAT2017/wp-content/uploads/2017/01/cfp_BDCAT2017.pdf