[hpc-announce] Call for Papers for the 7th IEEE/ACM Big Data Computing, Application Technology (BDCAT2020)

[De Maio, Vincenzo]

Call for Papers for the 7th IEEE/ACM Big Data Computing, Application Technology (BDCAT2020)

December 7-10, 2020 – Leicester, United Kingdom

https://www.cs.le.ac.uk/events/BDCAT2020/index.htm

Important Dates
Paper Submission Due: July 30, 2020
Notification of Acceptance: September 15, 2020
Camera-ready Paper Due: October 1, 2020
Early Author Registration Deadline: October 1, 2020
Conference: December 7-10, 2020

Context & Scope
During an era of unprecedented change we are faced with challenges that are well beyond traditional data-processing techniques. Big Data aims to ease analysis of large and varied data sets in a systematic fashion. Nowadays, Big Data is  the driving force for innovation that greatly impacts scientific, medical and socio-economic areas.
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.
BDCAT2020 will be hosted at the University of Leicester, UK. The city of Leicester is a major city in the middle of the country and is well connected to the rest of the world with road, rail and air networks.
This will be the 7th BDCAT in a successful conference series of community-driven events. Previous events were held in London, UK (BDCAT 2014), Limassol, Cyprus (BDCAT 2015), Shanghai, China (BDCAT 2016), Austin, Texas, USA (BDCAT 2017), Zurich, Switzerland (BDCAT 2018) and Auckland, New Zealand (BDCAT 2019).
BDCAT2020 is co-located with UCC2020 and offers a technical programme, workshops, tutorials, doctoral symposium, and cloud challenge.

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Authors are invited to submit original unpublished manuscripts on a broad range of topics related to big data science, computing paradigms, platforms and applications.
Topic of interest include (but 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

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:  https://easychair.org/conferences/?conf=bdcat2020
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 BDCAT2020 technical programme committee will select and acknowledge the best paper and the best student paper to receive an award during the conference.
Authors of highly rated papers from BDCAT2020 will be invited to submit an extended version to special issues of prestigious journals. Details will be announced soon.

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_______________________________________________
Dr. Vincenzo De Maio
Institute of Information Systems Engineering
Vienna University of Technology
Favoritenstr. 9-11, 1040 Vienna, Austria
Phone: +43 (1) 588 01 - 88737
Email: vincenzo at ec.tuwien.ac.at