2017 BIG DATA CONFERENCE
CALL FOR PAPERS

The 2017 Big Data Conference (formerly International Conference on Big Data and Its Applications) will continue the success of the previous Big Data conferences (ICBDA). It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications from business, technological and scientific points of view.

For the scientific track of the conference solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. Example topics of interest includes but is not limited to the following:

Big Data Science and Foundations
  • Novel Theoretical Models for Big Data
  • New Computational Models for Big Data
  • Data and Information Quality for Big Data
  • New Data Standards
Big Data Infrastructure
  • Cloud/Grid/Stream Computing for Big Data
  • High Performance/Parallel Computing Platforms for Big Data
  • Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
  • Energy-efficient Computing for Big Data
  • Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
  • Software Techniques and Architectures in Cloud/Grid/Stream Computing
  • Big Data Open Platforms
  • New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
  • Software Systems to Support Big Data Computing
Big Data Management
  • Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
  • Algorithms and Systems for Big Data Search
  • Distributed, and Peer-to-peer Search
  • Big Data Search Architectures, Scalability and Efficiency
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Visualization Analytics for Big Data
  • Computational Modeling and Data Integration
  • Large-scale Recommendation Systems and Social Media Systems
  • Cloud/Grid/Stream Data Mining- Big Velocity Data
  • Link and Graph Mining
  • Semantic-based Data Mining and Data Pre-processing
  • Mobility and Big Data
  • Multimedia and Multi-structured Data- Big Variety Data
Big Data Search and Mining
  • Social Web Search and Mining
  • Web Search
  • Algorithms and Systems for Big Data Search
  • Distributed, and Peer-to-peer Search
  • Big Data Search Architectures, Scalability and Efficiency
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Visualization Analytics for Big Data
  • Computational Modeling and Data Integration
  • Large-scale Recommendation Systems and Social Media Systems
  • Cloud/Grid/StreamData Mining- Big Velocity Data
  • Link and Graph Mining
  • Semantic-based Data Mining and Data Pre-processing
  • Mobility and Big Data
  • Multimedia and Multi-structured Data-Big Variety Data
Big Data Security,

Privacy and Trust
  • Intrusion Detection for Gigabit Networks
  • Anomaly and APT Detection in Very Large Scale Systems
  • High Performance Cryptography
  • Visualizing Large Scale Security Data
  • Threat Detection using Big Data Analytics
  • Privacy Threats of Big Data
  • Privacy Preserving Big Data Collection/Analytics
  • HCI Challenges for Big Data Security & Privacy
  • User Studies for any of the above
  • Sociological Aspects of Big Data Privacy
  • Trust management in IoT and other Big Data Systems
Big Data Security,

Privacy and Trust
  • Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
  • Big Data Analytics in Small Business Enterprises (SMEs)
  • Big Data Analytics in Government, Public Sector and Society in General
  • Real-life Case Studies of Value Creation through Big Data Analytics
  • Big Data as a Service
  • Big Data Industry Standards
  • Experiences with Big Data Project Deployments
  • Novel Theoretical Models for Machine Learning
  • New Computational Models for Artificial Intelligence
  • Data and Information Curation for Machine Learning
  • Cyber-Physical Systems
The language of the papers and

the oral presentation is English
Full paper up

to 9 pages
Deadline for full paper
submission – August 25
Registration fee for the confirmed

scientific track presenters is
15 000 ₽
(approximately $265)
  • The proceedings of the conference will be published in Journal of Physics: Conference Series (JPCS), and indexed by Web Of Science Conference Proceedings Index и Scopus.
  • Please submit full paper (up to 9 pages) at https://easychair.org/conferences/?conf=bdc2017
  • Important dates: August 25, 2017 – deadline for full paper submission
    September 10, 2017 – notification of acceptance
    September 15, 2017 – Conference
  • The language of the papers and the oral presentation is English.
  • Requirements for the article:
    The articles should be in strict accordance with the rules (page size - A4, margins - 4cm (top), 2.5cm (left and right) and 2.7cm (bottom)
    • Microsoft Word templates
    • Basic guidelines for preparing a paper
    • Guidelines for preparing reference lists

Conference Co-Chairs

Igor Balk
Global Innovation Labs, USA
Maria Podlesnova
Rusbase, Russia

Scientific track program committee

Igor Balk
Global Innovation Labs, USA
Andrey Raigorodsky
MIPT, Russia
Evgeny Niikulchev
MTI, Russia
Egor Mateshuk
Ostrovok, Russia
Danil Kirsanov
Microsoft, USA
Safronov Viktor
МFTI, Russia
Sozykin Andrey
IMM UB RAS
Should you have any questions feel free to contact us at


or at
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