[hpc-announce] DSEA 2021 CFP: The 5th International Workshop on Data Science Engineering and its Applications, Gandia, Spain. December 6-9, 2021

Stanley Ewenike stanley.ewenike92 at gmail.com
Mon Sep 27 13:43:48 CDT 2021

*The 5th International Workshop on Data Science Engineering and its
Applications (DSEA 2021)*


*In conjunction with **The 8th International Conference on Social Networks
Analysis, Management and Security(SNAMS-2021)*

* Gandia, Spain. December 6-9, 2021*

*DSEA 2021 CFP*

Today, Data is becoming an increasingly decisive resource in modern
societies, economies, and governmental organizations. Data science inspires
novel techniques and theories drawn from mathematics, statistics,
information theory, computer science, and social science. It involves many
domains, such as signal processing, probability models, machine learning,
data mining, database, data engineering, pattern recognition,
visualization, predictive analytic, data warehousing, data compression,
computer programming, etc. High Performance Computing typically deals with
smaller, highly structured data sets and huge amounts of computation. Data
Science has emerged to tackle the problem of creating processes and
approaches to extracting knowledge or insights from gigantic, unstructured
data sets.

The 5th International Workshop for Data Science Engineering and
Applications (DSEA 2021) aims to provide a forum that brings together
researchers, industry practitioners and domain experts for discussion and
exchange of ideas on the latest theoretical developments in Data Science
and Computing as well as on the best practices for a wide range of

The topics of interest for this workshop include, but are not limited to:

   - Architecture, management and process for Data Science
   - Big Data Mining and Knowledge Management
   - Evaluation and Measurement in Data Science
   - Privacy and protection standards and policies for Data Science
   - Data Quality
   - Data science for the internet of things (IoT)
   - Management Issues of Social Network Big Data
   - Big Data Computing for Data science
   - Social Network and Big Data Analytics
   - Open Source tools for Data Science and Big Data
   - Data Mining for Data science
   - High performance computing for data analytic

*Submissions Guidelines and Proceedings*

Manuscripts should be prepared in 10-point font using the IEEE 8.5" x 11"
two-column format (IEEE Templates
All papers should be in PDF format, and submitted electronically at Paper
Submission Link. A full paper must not exceed the stated length (including
all figures, tables and references). Submitted papers must present original
unpublished research that is not currently under review for any other
conference or journal. Papers not following these guidelines may be
rejected without review. Also submissions received after the due date,
exceeding length limit, or not appropriately structured may also not be
considered. Authors may contact the Program Chair for further information
or clarification.

All submissions are peer-reviewed by at least three reviewers. Accepted
papers will appear in the SNAMS Proceeding and to be submitted to IEEE
Xplore for inclusion. The proceedings are also submitted for indexing to EI
(Compendex), Scopus and other indexing services like DBLP.

Submitted papers must include original work, and must not be under
consideration for another conference or journal. Submission of regular
papers must not exceed 8 pages and must follow the IEEE paper format.
Please include up to 7 keywords, complete postal and e-mail address, and
fax and phone numbers of the corresponding author. Authors of accepted
papers are expected to present their work at the conference. Submitted
papers that are deemed of good quality but that could not be accepted as
regular papers will be accepted as short papers. Length of short papers

*Important Dates*

Submission Date: 5 Oct, 2021

Notification to Authors: 21 Oct, 2021

Camera Ready Submission: 30th Oct, 2021

Please send any inquiry to Emerging Tech. Network Team at:
emergingtechnetwork at gmail.com

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