2023 IEEE International Conference on Big Data (IEEE BigData 2023)
http://bigdataieee.org/BigData2023/
December 15-18, 2023
December 15-18, 2023 – Sorrento, Italy
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 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 IEEE Big Data 2020 ( http://bigdataieee.org/BigData2020/ , regular paper acceptance rate: 15.7%) was held online, Dec 10-13, 2020 with close to 1100 registered participants from 50 countries.
The IEEE Big Data 2021 ( http://bigdataieee.org/BigData2021/ , regular paper acceptance rate: 19.9%) was held online, Dec 15-18, 2021 with close to 1089 registered participants from 52 countries
The IEEE Big Data 2022 ( http://bigdataieee.org/BigData2022/ , regular paper acceptance rate: 19.2%) was held in Osaka, Japan, Dec 17-20, 2022 with close to 1250 registered participants from 54 countries.
The 2023 IEEE International Conference on Big Data (IEEE BigData 2023) 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 single-blind review policy. We expect to have a very high quality and exciting technical program at Sorrento, Italy this year. Example topics of interest includes but is not limited to the following:
1. 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
2. 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
3. Big Data Management
Data Acquisition, Integration, Cleaning, and Best Practices
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/Stream Data Mining- Big Velocity Data
Mobility and Big Data
Multimedia and Multi-structured Data- Big Variety Data
Compliance and Governance for Big Data
4. 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
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
5. Big Data Learning and Analytics
Predictive analytics on Big Data
Machine learning algorithms for Big Data
Deep learning for Big Data
Feature representation learning for Big Data
Dimension redution for Big Data
Physics informed Big Data learning
Visualization Analytics for Big Data
6. Data Ecosystem
Data ecosystem concepts, theory, structure, and process
Ecosystem services and management
Methods for data exchange, monetization, and pricing
Trust, resilience, privacy, and security issues
Privacy preserving Big Data collection/analytics
Trust management in Big Data systems
Ecosystem assessment, valuation, and sustainability
Experimental studies of fairness, diversity, accountability, and transparency
7. Big Data Applications
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
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-contribution 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/2023/bigdata23/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: Sept 3, 2023
Notification of paper acceptance: Oct 27, 2023
Camera-ready of accepted papers: Nov 17, 2023