Conference Information

BigData 2019: International Conference on Big Data

Please Login to view website of conference
Free account: view official websites, track deadlines, and get email reminders.
Register Login
Submission Date:
2022-08-20 Closed
Notification Date:
2022-10-25
Conference Date:
2019-12-09
Location:
Los Angeles, California, USA
Years:
7
Viewed: 41625   Tracked: 75   Attend: 28
Something wrong with this page? Tell us
Embed deadline badge
BigData
Get this via API
Search and ranking lists need no credentials at all; full detail for this page needs a free API key. See the developer guide.

Conference Partner Index (CP-I)

48.3 / 100
Ranked #2,147 of 5,771 conferences · Top 38%

#125 of 340 in Data Mining & Databases

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
56
Community attention (10%)
58
Public record completeness (15%)
25

Inputs used: Editions on record: 7 · Researchers following it here: 75 · Researchers who opened this page in the past 24 months: 8

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.2 · Computed 2026-11-09

Researchers at these institutions track this conference

Tsinghua University 5
Beijing University of Posts and Telecommunications 4
Institute of Information Engineering, Chinese Academy of Sciences 4
Southwest University 4
Beihang University 3
East China Normal University 3
Peking University 3
Shanghai Jiao Tong University 3

Based on the institution researchers enter on their own profiles. We do not verify it.

Call For Papers

BigData 2019 (International Conference on Big Data) is an academic conference held in Los Angeles, California, USA on 2019-12-09. The paper submission deadline is 2022-08-20 (extended). Acceptance notifications are sent on 2022-10-25.

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 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 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 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 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 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 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 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). 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/scripts/submit.php?subarea=BigD Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to "formatting instructions" below).
Last updated by Mono Zhong on

Related Conferences

CCFICORECP-IShortFull NameSubmissionConference
48.4BigData''International Conference on Big Data2026-05-212026-08-22
CB56.6IEEE BigDataIEEE International Conference on Big Data2026-08-212026-12-14
41.7BigData'ASE International Conference on Big Data2015-07-282015-10-07
46.5BigData CongressInternational Congress on Big Data2019-03-022019-07-08
39.8Big DataInternational Conference on Big Data2014-04-302014-08-04
43.4IEEE Big Data ServiceIEEE International Conference On Big Data Service and Applications2018-11-302019-04-04
C56.7DATAInternational Conference on Data Science, Technology and Applications2027-03-252027-07-19
38.7Data'International Conference on Data Science, E-learning and Information Systems2019-04-152019-12-02
AA*96.0SIGIRInternational Conference on Research and Development in Information Retrieval2027-01-142027-07-18
AA*97.8AAAIAAAI Conference on Artificial Intelligence2026-07-212027-02-16

Related Journals

CCFFull NameImpact FactorPublisherISSN
Journal of Big Data6.4Springer2196-1115
Big Data Research4.2Elsevier2214-5796
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.5Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203

Comments 0

No comments yet.

Please Login to post a comment