Call for Papers
Context & Scope
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 5 events were held in London, Cyprus, Shanghai, Austin and Zurich.
BDCAT2019 will be held in conjunction with the 11th IEEE/ACM International Conference on Utility and Cloud
Computing at Auckland University of Technology in the heart of New Zealand's city of sails.
Call for Papers
Authors are invited to submit original unpublished manuscripts on a broad range of topics related to big data science,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
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
Manuscript Guidelines and Submission
Submitted manuscripts must represent original unpublished research that is not currently
under review for any other conference or journal.
Manuscripts are submitted in PDF format and may not exceed ten single-spaced double-column
pages using 10-point size font on 8.5x11 inch pages, including figures, tables, and references.
Please refer to http://www.acm.org/publications/proceedings-template for
templates and complete formatting instructions.
Manuscripts are submitted via the Easychair Conference Management System:
All manuscripts will be reviewed and judged on correctness, originality,
technical strength, rigour in analysis, quality of results, quality of presentation, and
interest and relevance to the conference attendees.
The conference proceedings will be published by the ACM and
made available online via the ACM Digital Library and IEEE Digital Library.
Awards and Special Issues
A selection commission chaired by the BDCAT2019 technical programme committee will select and
acknowledge the best paper and best student paper to receive an award during the conference.
Authors of highly rated papers from BDCAT2019 will be invited to submit an extended version
to a special issue of the prestigious Journal of Cloud Computing and published online by SpringerOpen.