BDCAT 2018 : 5th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
Call For Papers
The IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT) is an annual conference series aiming 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 4 events were held in London, Cyprus, Shanghai, and Austin. BDCAT 2018 will be held in conjunction with the 11th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2018) in Zurich, Switzerland.
Authors are invited to submit original unpublished manuscripts on a broad range of topics related to big data science, computing paradigms, platforms and applications.
Topics of interest include, but are not limited to:
I. 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
- Big Data and Deep Learning
II. Big Data Infrastructures and Platforms
- Scalable Computing Models, Theories, and Algorithms
- In-Memory Systems and Platforms for Big Data Analytics
- Big Data and High Performance Computing
- 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
III. 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
IV. 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
V. 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
Manuscripts shall be formatted in IEEE conference style and may not exceed ten pages. In detail, 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 IEEE templates. Papers should be prepared in two-column single-spaced format. 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 2018 paper submission system (URL to be provided in March 2018).
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 TPC Chairs for more information.
A selection commission chaired by the BDCAT 2018 TPC chairs will select and acknowledge the best paper and best student paper to receive an award during the conference.
Authors of highly rated papers from BDCAT 2018 will be invited to submit an extended version to a special issue of a prestigious journal in the area of big data which is currently being defined.