According to NIST framework for Big Data processing, data preparation or curation is an important cornerstone and an early stage to support big data analysis. Generally speaking, data preparation techniques are focused on cleansing, compressing and organizing etc. Especially, under the theme of Cyber-Physical-Social systems where complicated distributed and paralleled systems or platforms (such as WSN or Cloud) are widely involved, the big data preparation and curation should be intensively discussed with more concern about scalability and dependability. In terms of scalable and dependable big data cleansing, approaches are expected to solve the problems including error classification, error detection, error recovery and redundancy etc. In terms of scalable and dependable big data compressing and organizing, independent techniques are expected to be developed to reduce the size of big data, hence, to avoid massive storage and finally to find a way for efficient data organizing.

This special session aims to publish the latest research advancement in big data preparation/curation. We welcome papers reporting theoretical or real-world progress of big data processing technologies with more scalability and dependability under the framework of Cyber-Physical-Social systems.

This is a special session of the 13th IEEE International Conference on Cyber, Physical and Social Computing (http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php). Please submit your paper via the submission site (TBA) and select the special session of “Preparation/Curation Techniques for Big Data in Cyber-Physical-Social Systems” marked with “CPSComPCTBD”.

Accepted conference papers will be published by IEEE (IEEE-DL and EI indexed). Selected papers, after further extensions and revisions, will be recommended to journal special issues. More details at the conference website:
http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php

Potential topics include but are not limited to:

•    scalable and dependable big data preparation/curation techniques
•    scalable and dependable big data processing techniques
•    big data compression
•    big data cleansing
•    normalization techniques
•    dependable massive data processing models, tools and platforms
•    novel framework and platform for big data scalable processing
•    Cross platform big data processing techniques and tools
•    Cyber-security issue for big data in CPSS
•    Seamless data integration between IoT big data
•    Visualization for big data processing
•    Big data processing and IoT

Session Chairs：
Chi Yang, Huazhong University of Science and Technology, China
Meng Liu, Shandong University, China