The 2017 IEEE International Conference on Smart Data
(SmartData-2017)
21-23 June 2017
Exeter, Devon, UK

Smart Data aims to filter out the noise and produce the valuable data, which can be effectively used by enterprises and governments for planning, operation, monitoring, control, and intelligent decision making. Although unprecedentedly large amount of sensory data can be collected with the advancement of the Cyber Physical Social (CPS) systems recently, the key is to explore how Big Data can become Smart Data and offer intelligence. Advanced Big Data modeling and analytics are indispensable for discovering the underlying structure from retrieved data in order to acquire Smart Data. The goal of this conference is to promote community-wide discussion identifying the Computational Intelligence technologies and theories for harvesting Smart Data from Big Data.

Scope and Topics

The goal of The 2017 IEEE International Conference on Smart Data (SmartData-2017) is to provide a forum for scientists, engineers and researchers to discuss and exchange novel ideas, results, experiences and work-in-process on all aspects of Smart Data.

Topics of interest include, but are not limited to:

Track 1: Data Science and Its Foundations

Foundational Theories for Data Science
Theoretical Models for Big Data
Foundational Algorithms and Methods for Big Data
Interdisciplinary Theories and Models for Smart Data
Data Classification and Taxonomy
Data Metrics and Metrology

Track 2: Big Data Infrastructure and Systems

Cloud/Cluster Computing for Big Data
Programming Models/Environments for Cluster/Cloud Computing
High Performance/Throughtput Platforms for Big Data Computing
Parallel Computing for Big Data
Open Source Big Data Systems (e.g., including Hadoop, Spark, Flink and Storm)
System Architecture and Infrastructure of Big Data
New Programming Models for Big Data beyond Hadoop/MapReduce
Big Data Appliance
Big Data Ecosystems

Track 3: Big Data Storage and Management

Big Data Collection, Transformation and Transmission
Big Data Integration and Cleaning
Uncertainty and Incompleteness Handling in Big Data/Smart Data
Quality Management of Big Data/Smart Data
Big Data Storage Models
Query and Indexing Technologies
Distributed File Systems
Distributed Database Systems
Large-Scale Graph/Document Databases
NewSQL/NoSQL for Big Data

Track 4: Big Data Processing and Analytics

Smart Data Search, Mining and Drilling from Big Data
Semantic Integration and Fusion of Multi-Source Heterogeneous Big Data
In-Memory/Streaming/Graph-Based Computing for Big Data/Smart Data
Brain-Inspired/Nature-Inspired Computing for Big Data/Smart Data
Distributred Representation Learning of Smart Data
Machine Learning/Deep Learning for Big Data/Smart Data
Applications of Conventional Theories (e.g., Fuzzy Set, Rough Set, and Soft Set) in Big Data
New Models, Algorithms, and Methods for Big/Smart Data Processing and Analytics
Exploratory Data Analysis
Visualization Analytics for Big Data
Big Data Based Prediction Methods
Big Data Aided Decision-Marking

Track 5: Big/Smart Data Applications

Big/Smart Data Applications in Science, Internet, Finance, Telecommunictions, Business, Medicine, Healthcare, Government, Transportation, Industry, Manufacture
Big/Smart Data Applications in Government and Public Sectors
Big/Smart Data Applications in Enterprises
Security, Privacy and Trust in Big Data
Big Data Opening and Sharing
Big Data Exchange and Trading
Data as a Service (DaaS)
Standards for Big/Smart Data
Case Studies of Big/Smart Data Applications
Practices and Experiences of Big Data Project Deployments
Ethic Issues about Big Data Applications

Important Dates:

• Workshop/Special Session Proposal Due:15 December 2016
  
• Paper Submission Deadline:23 February 2017
  
• Authors Notification:22 April 2017
  
• Camera-Ready Paper Due:15 May 2017
  
• Early Registration Due:15 May 2017
  

User Name : shaun
Posted 02-12-2016 on 12:33:39 AEDT

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