Conference Information
BigDataSE 2020: International Conference on Big Data Science and Engineering
http://www.ieee-trustcom.org/BigDataSE2020/
Submission Date:
2020-08-15 Extended
Notification Date:
2020-09-29
Conference Date:
2020-12-29
Location:
Guangzhou, China
Years:
14
Viewed: 11113   Tracked: 13   Attend: 0

Conference Location
Call For Papers
Introduction

Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud computing platforms, and MapReduce.

BigDataSE 2020 topics include, but are not limited to the following:

    Systems, Models and Algorithms
    Big Data novel theory, algorithm and applications
    Big Data standards
    Big Data mining and analytics
    Big Data Infrastructure, MapReduce and Cloud Computing
    Big Data visualization
    Big Data curation and management
    Big Data semantics, scientific discovery and intelligence
    Big Data performance analysis and large-scale deployment
    Security, privacy, trust, and legal issues to big data
    Big Data vs Big Business and Big Industry
    Large data stream processing on cloud
    Large incremental datasets on cloud
    Distributed and federated datasets
    NoSQL data stores and DB scalability
    Big Data placement, scheduling, and optimization
    Distributed file systems for Big Data
    MapReduce for Big Data processing, resource scheduling and SLA
    Performance characterization, evaluation and optimization
    Simulation and debugging systems and tools for MapReduce and Big Data
    Volume, Velocity, Variety, Value and Veracity of Big Data
    Multiple source data processing and integration with MapReduce
    Storage and computation management of Big Data
    Large-scale big data workflow management
    Mobility and big data
    Sensor network, social network and big data
    Big data applications

Submission and Publication Information

All papers need to be submitted electronically through the conference website (https://easychair.org/conferences/?conf=BigDataSE2020) with PDF format. Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. A submission is limited to 8 pages for main conference regular papers, 6 pages for workshop papers or short papers in the IEEE Computer Society Proceedings Format with Portable Document Format (.pdf). A submission can have at most 4 additional pages with the pages overlength charge if accepted. Papers must be clearly presented in English, including tables, figures, references and appendices. Papers will be selected based on their originality, significance, relevance, and clarity of presentation assessed by at least three reviewers. Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work. BigDataSE 2020 reserves the right to exclude a paper from distribution after the conference (e.g., removal from the digital library and indexing services), if the paper is not presented at the conference. Accepted and presented papers will be included in the IEEE CPS Proceedings. Distinguished papers presented at the conference, after further revision, will be published in special issues of high quality international journals.Two or three outstanding papers will be selected to receive the Best Paper Awards. 
Last updated by Dou Sun in 2020-08-10
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