Call for Papers

2022 IEEE International Conference on Big Data  (IEEE BigData 2022)

http://bigdataieee.org/BigData2022/

December 17-20, 2022 – Osaka, Japan

(may move to hybrid or online depending on the pandemic situation by then)

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 2019 (http://bigdataieee.org/BigData2019/  ,  regular paper acceptance rate: 18.7%) was held in Los Angeles, CA, Dec 9-12, 2019 with close to 1200 registered participants from 54 countries.

·       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 2022 IEEE International Conference on Big Data (IEEE BigData 2022) 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 Osaka, Japan  this year. Example topics of interest includes but is not limited to the following:

1.     Big Data Science and Foundations

a.      Novel Theoretical Models for Big Data

b.     New Computational Models for Big Data

c.      Data and Information Quality for Big Data

d.     New Data Standards

2.     Big Data Infrastructure

a.      Cloud/Grid/Stream Computing for Big Data

b.     High Performance/Parallel Computing  Platforms for Big Data

c.      Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment

d.     Energy-efficient Computing for Big Data

e.      Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data

f.      Software Techniques and Architectures in Cloud/Grid/Stream Computing

g.     Big Data Open Platforms

h.     New Programming Models for Big Data beyond Hadoop/MapReduce, STORM

i.       Software Systems to Support Big Data Computing

3.     Big Data Management

a.      Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data

b.     Algorithms and Systems for Big DataSearch

c.      Distributed, and Peer-to-peer Search

d.     Big Data Search  Architectures, Scalability and Efficiency

e.      Data Acquisition, Integration, Cleaning,  and Best Practices

f.      Visualization Analytics for Big Data

g.     Computational Modeling and Data Integration

h.     Large-scale Recommendation Systems and Social Media Systems

i.       Cloud/Grid/Stream Data Mining- Big Velocity Data

j.       Link and Graph Mining

k.     Semantic-based Data Mining and Data Pre-processing

l.       Mobility and Big Data

m.   Multimedia and Multi-structured Data- Big Variety Data

4.     Big Data Search and Mining

a.      Social Web Search and Mining

b.     Web Search

c.      Algorithms and Systems for Big Data Search

d.     Distributed, and Peer-to-peer Search

e.      Big Data Search  Architectures, Scalability and Efficiency

f.      Data Acquisition, Integration, Cleaning,  and Best Practices

g.     Visualization Analytics for Big Data

h.     Computational Modeling and Data Integration

i.       Large-scale Recommendation Systems and Social Media Systems

j.       Cloud/Grid/StreamData Mining- Big Velocity Data

k.     Link and Graph Mining

l.       Semantic-based Data Mining and Data Pre-processing

m.   Mobility and Big Data

n.     Multimedia and Multi-structured Data- Big Variety Data

5.      Big Data Learning and Analytics

a.      Predictive analytics on Big Data

b.     Machine learning algorithms for Big Data

c.      Deep learning for Big Data

d.     Feature representation learning for Big Data

e.      Dimension reduction for Big Data

f.       Physics informed Big Data learning

6.     Data Ecosystem

a.      Data ecosystem concepts, theory, structure, and process

b.     Ecosystem services and management

c.      Methods for data exchange, monetization, and pricing

d.     Trust, resilience, privacy, and security issues

e.      Privacy preserving Big Data collection/analytics

f.      Trust management in Big Data systems

g.     Ecosystem assessment, valuation, and sustainability

h.     Experimental studies of fairness, diversity, accountability, and transparency

7.     Big Data Applications

a.      Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication

b.     Big Data Analytics in Small Business Enterprises (SMEs),

c.      Big Data Analytics in Government, Public Sector and Society in General

d.     Real-life Case Studies of Value Creation through Big Data Analytics

e.      Big Data as a Service

f.      Big Data Industry Standards

g.   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/2022/bigdata22/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

Visa Application:

Japan has opened its border to allow foreigners to visit Japan, IEEE BigData 2022 has hired a Japanese company to assist all participants from over the world to get a visa to enter Japan for the conference. The visa application process is very smooth and detailed information is already posted in the conference website.

Important Dates:

Electronic submission of full papers: Sept 3, 2022

Notification of paper acceptance: Oct 25, 2022

Camera-ready of accepted papers: Nov 15, 2022

Conference: Dec 17-20, 2022