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Important dates

Abstract submission April 15, 2022
Workshop proposals March 31, 2022
Full paper submission April 29, 2022
Paper acceptance notification June 8, 2022
Camera-ready and registration June 22, 2022
Main conference August 15-18, 2022

As computing systems become increasingly larger, more complex, distributed, and integrated, Big Data technologies and services are ever more vital. IEEE BigDataService 2022 provides an internationally leading forum for researchers and practitioners in academia and industry to exchange innovative ideas and share latest results, experiences and lessons learned in this crucial domain.

The conference will take place in the San Francisco Bay Area (California, USA) on the 22nd-25th of August 2022, and will consist of a main track and special tracks. The conference also welcomes workshop proposals and seeks the submission of high-quality papers limited to up to 8 pages (IEEE format) in length. All accepted papers will be included in the proceedings. Selected papers will be invited for extension and published in journals (SCI-Index).

BigDataService 2022 is part of the CISOSE 2022 congress, and it will be co-located with IEEE SOSE 2022, IEEE MobileCloud 2022, IEEE DAPPS 2022, and IEEE AITest 2022.

Topics of Interest (but not limited to)

Big Data Analytics and Machine Learning

  • Algorithms and systems for big data search and analytics
  • Machine learning for big data and based on big data
  • Predictive analytics and simulation
  • Visualization systems for big data
  • Knowledge extraction, discovery, analysis, and presentation

Integrated and Distributed Systems

  • Sensor networks
  • Internet of Things
  • Networking and Protocols
  • Smart systems (energy efficient systems, smart homes, smart farms, etc.)

Big Data Platforms and Technologies

  • Innovative, concurrent, and scalable big data platforms
  • Data indexing, cleaning, transformation, and curation technologies
  • Big data processing frameworks and technologies
  • Big data services and application development methods and tools
  • Big data quality evaluation and assurance technologies
  • Big data system reliability, dependability, and availability
  • Open-source development and technology for big data
  • Big Data as a Service (BDaaS) platform and technologies

Big Data Foundations

  • Foundational theoretical or computational models for big data
  • Programming models, theories, and algorithms for big data
  • Standards, protocols, and quality assurance for big data

Big Data Applications and Experiences

  • Innovative big data applications and services in industries and domains e.g. healthcare, finance, insurance, transportation, agriculture, education, environment, multi-media, social networks, urban planning, disaster management, security
  • Experiences and case studies of big data applications and services
  • Real-world and large-scale practices of big data

Special Track on Real-time Big Data Services and Applications

  • Models, algorithms, and technologies for real-time big data services and applications
  • Experiences, practices and case studies of real-time big data services and applications

Special Track on Big Data Security, Privacy, Trust, and Sustainability

  • Models, algorithms and technologies for big data security and privacy
  • Attacks and defenses for big data services
  • Privacy-preserving processing of big data and Big Data for Security and Privacy Analysis
  • Energy-aware big data storage, transfer, and usage
  • AI-continuum (e.g., cloud, edge, sensors) for sustainable Big data services

Special Track on Big Data and Analytics for Healthcare

  • Models, algorithms, and technologies of big data for healthcare
  • Big data services and applications for healthcare
  • Experiences, practices and case studies of big data technologies for healthcare

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