Abbrevation
SmartData
City
Atlanta
Country
United States
Deadline Paper
Start Date
End Date
Abstract

<font color="#000066"><font color="#000000">Smart Data aims to filter out the noise and produce valuable data, which can be effectively used by enterprises and governments for planning, operation, monitoring, control, and intelligent decision making&#046; Although unprecedentedly large amount of sensory data can be collected with the advancement of the Cyber&#8211;Physical&#8211;Social systems, the key is to explore how Big Data can become Smart Data and offer intelligence&#046; Advanced Big Data modeling and analytics are indispensable for discovering the underlying structure from retrieved data and further acquiring Smart Data&#046;<br>The 2019 IEEE International Conference on Smart Data (SmartData&#8211;2019) is to promote community&#8211;wide discussion identifying the computational intelligence technologies and theories for harvesting Smart Data from Big Data&#046; It will provide a high&#8211;profile, leading&#8211;edge forum for scientists, engineers and researchers to discuss and exchange novel ideas, results, experiences and work&#8211;in&#8211;process on all aspects of Smart Data&#046;<br>==============================================<br>Topics of interest include, but are not limited to the following:<br>==============================================<br>Track 1: Data Science and Its Foundations<br>&#8211;Foundational Theories for Data Science<br>&#8211;Theoretical Models for Big/Smart Data<br>&#8211;Data inference for Big/Smart Data<br>&#8211;Data Classification and Taxonomy<br>&#8211;Data Metrics and Metrology<br>Track 2: Big/Smart Data Infrastructure and Systems<br>&#8211;Cloud/Cluster/Fog/Edge Computing for Big Data<br>&#8211;Parallel Computing for Big Data<br>&#8211;Open Source Big Data Systems (e&#046;g&#046;, including Hadoop, Spark, Flink and Storm)<br>&#8211;System Architecture and Infrastructure of Big/Smart Data<br>&#8211;Big/Smart Data Appliance<br>Track 3: Big/Smart Data Storage and Management<br>&#8211;Big/Smart Data Collection, Transformation and Transmission<br>&#8211;Big/Smart Data Integration, Cleaning and Storage<br>&#8211;Data Query and Indexing Technologies<br>&#8211;Distributed File/Database Systems<br>&#8211;NewSQL/NoSQL for Big/Smart Data<br>Track 4: Big/Smart Data Processing and Analytics<br>&#8211;Smart Data Search, Mining and Drilling from Big Data<br>&#8211;Data Mining/Machine Learning/Deep Learning for Big/Smart Data<br>&#8211;In&#8211;Memory/Streaming/Graph&#8211;Based Computing for Big/Smart Data<br>&#8211;Brain/Nature&#8211;Inspired Computing for Big/Smart Data<br>&#8211;Secure/Privacy&#8211;Preserving/Differentially Private Computing for Big/Smart Data<br>&#8211;New Models, Algorithms, and Methods for Big/Smart Data Analytics<br>&#8211;Visualization Analytics for Big Data<br>Track 5: Big/Smart Data Applications<br>&#8211;Big/Smart Data Applications in All Fields, e&#046;g&#046;, Finance, Business, Healthcare, Transportation, Industry, Manufacture, Education, Telecommunication, etc&#046;<br>&#8211;Data as a Service (DaaS)<br>&#8211;Security, Privacy and Trust in Big/Smart Data<br>&#8211;Blockchain&#8211;Based Applications in Big/Smart Data<br>&#8211;Big/Smart Data Opening, Sharing, Exchange and Trading<br>&#8211;Practices and Experiences of Big/Smart Data Project Deployments<br>&#8211;Ethic Issues in Big/Smart Data Applications<br></font></font>