IEEE BigData

2026 IEEE International Conference on Big Data

Call for Papers

IEEE Big Data 2026 Call for Papers

2026 IEEE International Conference on Big Data (IEEE BigData 2026) – Dec 14-17, 2026, Phoenix, AZ, USA (https://bigdataieee.org/BigData2026)

In recent years, "Big Data" has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data.

  • The IEEE Big Data 2025 (http://bigdataieee.org/BigData2025/, regular paper acceptance rate: 18%) was held at Macau, USA, Dec 5 – 8, 2025 with more than 1200 registered participants from 54 countries
  • The IEEE Big Data 2024 (http://bigdataieee.org/BigData2024/, regular paper acceptance rate: 18.4%) was held at Washington DC, USA, Dec 15-18, 2024 with more than 1300 registered participants from 53 countries
  • The first conference, IEEE Big Data 2013, had more than 400 registered participants from 40 countries ( http://bigdataieee.org/BigData2013/), and the regular paper acceptance rate is 17.0%.

The 2026 IEEE International Conference on Big Data (IEEE BigData 2026) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications.

We 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. The conference adopts a single-blind review policy. We expect to have a very high-quality and exciting technical program at Sorrento, Italy, this year.

Topics of Interest:

  • Big Data Science and Foundations
    • New Data Standards
    • Data and Information Quality for Big Data
    • New Computational Models for Big Data
    • Novel Theoretical Models for Big Data
  • Big Data Infrastructure
    • Software Systems to Support Big Data Computing
    • New Programming Models for Big Data beyond Hadoop /MapReduce, STORM
    • Big Data Open Platforms
    • Software Techniques and Architectures in Cloud /Grid /Stream Computing
    • Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
    • Energy-efficient Computing for Big Data
    • Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
    • High Performance /Parallel Computing Platforms for Big Data
    • Cloud /Grid /Stream Computing for Big Data
  • Big Data Management
    • Compliance and Governance for Big Data
    • Multimedia and Multi-structured Data- Big Variety Data
    • Mobility and Big Data
    • Cloud/Grid/Stream Data Mining- Big Velocity Data
    • Large-scale Recommendation Systems and Social Media Systems
    • Computational Modeling and Data Integration
    • Data Acquisition, Integration, Cleaning, and Best Practices
  • Big Data Search and Mining

    Search and Mining of a variety of data,

    • multimedia data.
    • social, sensor /IoT /IoE, and
    • including scientific and engineering,
  • Data Ecosystem
    • Experimental studies of fairness, diversity, accountability, and transparency
    • Ecosystem assessment, valuation, and sustainability
    • Trust management in Big Data systems
    • Privacy preserving Big Data collection/analytics
    • Trust, resilience, privacy, and security issues
    • Methods for data exchange, monetization, and pricing
    • Ecosystem services and management
    • Data concepts, theory, structure, and process
  • Foundation Models for Big Data
    • Foundation Model Operationalization for multiple users
    • Prompt Engineering and its Management
    • Big data management for prompt-tuning
    • Big data management for fine-tuning
    • Big data management for pre-training
  • Big Data Applications

    Complex Big Data Domain Applications in

    • Engineering
    • Human Resources
    • Cybersecurity
    • Industrial IoT
    • Media and Entertainment
    • Telecommunication
    • Advertising
    • Marketing
    • Supply Chains
    • Retailing
    • Transportation
    • Logistics
    • Education
    • Law
    • Business
    • Finance
    • Urban Planning
    • Smart Cities
  • Big Data for Science
    • Science Knowledge Foundation Models
    • AI-accelerated Simulations and Modeling
    • AI-Ready Scientific Big Data Systems and Analysis
    • Medicine and Health Science
    • Chemical Engineering and Synthetic Biology
    • Materials Informatics
    • Geospatial and Planetary Analytics
    • Climate and Earth Sciences
    • Genomics and Bioinformatics, Structural Biology Science
    • Computational Astrophysics
    • AI-Driven Scientific Discovery in Physical Sciences
  • Big Data Benchmarks
    • Responsible Dataset Development
    • Advanced Collection and Curation Practices
    • Data-Centric AI Methods, Tools, and Systems
    • Data Generators and Synthetic Environments
    • Benchmarking Tools and Platforms
    • Benchmarks and Evaluation Frameworks
    • New Datasets and Collections
  • Big Data BlueSky Ideas
    • Novel Interdisciplinary Synthesis
    • Paradigm-Shifting Applications
    • Foundational Assumption Challenges
    • New Algorithmic Opportunities
    • Complex and Hard Problem Solving
    • Trending, Emerging, Bold, or Visionary Concepts

Industrial & Government Track

The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages).

The Government Track welcomes papers discussing the usefulness and need for publicly contributed big data and open data, and their use. Specifically, data utilization scenarios, needs analysis, data utilization obstacle analysis and solutions, data integration processes, interfaces as data utilization solutions, visualization, use cases, evidence-based policy making, building an ecosystem for solving social issues, analyzing their cases, comparing international and regional differences, and conducting comparative surveys before and after specific events (like Covid-19). We are also looking for other big data solutions related to national and local governments and public services.

Please submit an extended abstract (2-4 pages) OR a full-length paper (up to 10 pages) through the online submission page (Industrial & Government Track dedicated page)

Paper Submission:

Please submit a full-length paper (up to 10 page IEEE 2-column format, reference pages counted in the 10 pages) through the online submission system.

https://wi-lab.com/cyberchair/2026/bigdata26/index.php

Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to "formatting instructions" below). https://www.ieee.org/conferences/publishing/templates.html

Important Dates:

  • Electronic submission of full papers: Aug. 21, 2026
  • Notification of paper acceptance: Oct. 24, 2026
  • Camera-ready of accepted papers: Nov. 14, 2026
  • Conference: Dec 14-17, 2026