[hpc-announce] Call for book chapters "Smart Data: State-of-the-Art and Perspectives in Computing and Applications"

[Kuan-Ching Li]

*** Apologies if multiple copies of this call are received ****


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Call for Book Chapters
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Smart Data: State-of-the-Art and Perspectives in Computing and Applications
(Chapman & Hall/ CRC Big Data Series)
CRC Press, Taylor & Francis Group, USA

Important Dates
* Proposal Submission: February 1, 2018*
* Proposal (Acceptance/Rejection): February 15, 2018
* Sample Chapter (Acceptance/Rejection): April 15, 2018
* Complete Chapter Submission (to editors):   June 15, 2018
* Submission of Chapters (to publisher): July 1, 2018
* Publication Time: Q4/2018 (estimated)

Big Data is being generated around us at 24/7 basis, from daily business,
custom use, engineering, science activities, sensory data collected from
IoTs and CPS systems, among others. Storing and owing only such massive
amount of data is meaningless, as the key point is to identify, locate and
extract valuable knowledge from Big Data to forecast and services support,
improving quality of service and society’s value. Such extracted valuable
knowledge is usually referred to Smart Data that is vital in providing
suitable decision in highly on-demand business, science and engineering
applications.
How to select Smart Data from Big Data, unlocking value in massive
datasets? Advanced Big Data modeling and analytics are indispensable for
discovering the underlying structure from retrieved data to acquire Smart
Data, whereas novel computing theories as well advanced mining and learning
techniques are fundamentally important to the search of such intelligent
decision and predicative services support.

In this book, it is intended to invite scholars, experts and successful
case participating members to contribute discussions on topics for smart
data mining and management as well as applications. Not only smart data
computing algorithms and architectures from the computer point of view, but
also smart data applications in business issues aspects, industrial aspects
and related areas, it is equally well suitable for data analysts in
business and industry.

* Topics
Topics include, but are not limited to, the following:

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: Smart Data Infrastructure and Systems
- Programming Models/Environments for Cluster/Cloud/Edge/BigData Computing
- High Performance/Throughtput Platforms for Smart/Big Data Computing
- Cloud Computing, Edge Computing and Fog Computing for Smart/Big Data
- System Architecture and Infrastructure of Smart/Big Data
- New Programming Models for Smart/Big Data beyond Hadoop/MapReduce
- Smart Data Appliance
- Smart Data Ecosystems

Track 3: Big Data Storage and Management
- Smart Data Collection, Transformation and Transmission
- Big Data Integration and Cleaning for Smart Data
- Uncertainty and Incompleteness Handling in Smart/Big Data
- Quality Management of Smart/Big Data
- Smart Data Storage Models
- Query and Indexing Technologies
- Distributed File Systems
- Distributed Database Systems
- Large-Scale Graph/Document Databases

Track 4: Smart 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 Smart/Big Data
- Brain-Inspired/Nature-Inspired Computing for Smart/Big Data
- Distributed Representation Learning of Smart Data
- Machine Learning/Deep Learning for Smart/Big Data
- Applications of Conventional Theories (e.g., Fuzzy Set, Rough Set) in
Smart/Big Data
- New Models, Algorithms, and Methods for Smart/Big Data Processing and
Analytics
- Exploratory Data Analysis
- Visualization Analytics for Big Data
- Smart/Big Data Aided Decision-Marking

Track 5: Smart/Big Data Applications
- Smart/Big Data Applications in Science, Internet, Finance,
Telecommunications, Business, Medicine, Healthcare, Government,
Transportation, Industry, Manufacture
- Smart/Big Data Applications in Government and Public Sectors
- Smart/Big Data Applications in Enterprises
- Security, Privacy and Trust in Smart/Big Data
- Smart/Big Data Opening and Sharing
- Smart/Big Data Exchange and Trading
- Data as a Service (DaaS)
- Standards for Smart/Big Data
- Case Studies of Smart/Big Data Applications
- Practices and Experiences of Smart/Big Data Project Deployments
- Ethic Issues on Smart/Big Data Applications

* Proposal submission
A proposal for book chapter is needed from prospective authors before the
proposal *submission due date*, describing the objective, scope and
structure of the proposed chapter (no more than 5 pages). Acceptance of
chapter proposals will be communicated to lead chapter authors after a
formal double-blind review process, to ensure relevance, quality and
originality. The submission of chapter proposals should be sent directly
via email to editors.

* Book Editors
Kuan-Ching Li, Providence University, Taiwan, kuancli at gm.pu.edu.tw
Qingchen Zhang, St. Francis Xavier University, Canada, qzhang at stfx.ca
Laurence T. Yang, St. Francis Xavier University, Canada, ltyang at gmail.com
Beniamino Di Martino, Universita' della Campania "Luigi Vanvitelli", Italy,
beniamino.dimartino at unicampania.it

* Additional Information
Inquiries and chapter proposal submissions can be forwarded electronically
by email, to:
Qingchen Zhang (email: qzhang at stfx.ca), cc'ied to kuancli at gm.pu.edu.tw,
ltyang at gmail.com and beniamino.dimartino at unicampania.it
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