Paper submission due:
August
25, 2015 (firm)
Author notification:
September25, 2015
Camera Ready due:
October 15, 2015
Registration due:
October 15, 2015
Scope and Topics
Introduction
In parallel with
Petrol as a driving resource in this
world,
Data is becoming an increasingly
decisive resource in modern
societies, economies, and
governmental organizations.
Gradually and steadily, it is being
world-wide recognised that data and
talents are playing key roles in
modern businesses.
As an
interdisciplinary area, Data Science
draws scientific inquiry from a
broad range of subject areas such as
statistics, mathematics, computer
science, machine learning,
optimization, signal processing,
information retrieval, databases,
cloud computing, computer vision,
natural language processing and etc.
Data Science is on the essence of
deriving valuable insights from
data. It is emerging to meet the
challenges of processing very large
datasets, i.e. Big Data, with the
explosion of new data continuously
generated from various channels such
as smart devices, web, mobile and
social media.
Data intensive
systemsare posing
many challenges in exploitingparallelism of current and
upcoming computer architectures.
Data volumesof applications in the fields
of sciences and engineering,
finance,
media, online information resources,
etc. are expected to double everytwo years over the next
decade and
further. With this continuing dataexplosion, it is necessary to
store and process data efficiently
by
utilizing enormous computing power.
The
importance of data intensive
systems
hasbeen
raising and will continue to be the
foremost fields of research.This raise brings up many
research issues, in forms of
capturing andaccessing data effectively
and fast, processing it while still
achieving
high performance and high
throughput, and storing it
efficiently forfuture use.
Innovative
programming models, high performance
scalable computing platforms,
efficient storage systems and
expression of data requirements are
at immediate need.
DSDIS
(Data Science and
Data Intensive Systems)
was created to provide a prime
international forum for researchers,
industry practitioners and domain
experts to exchange the latest
advances in Data
Science and Data Intensive Systems as
well as their synergy.
Scope and Topics
A. Data Science
Topics of particular interest
include, but are not limited to:
•
Data sensing,
fusion and mining
•
Data
representation, dimensionality
reduction, processing and proactive
service layers
•
Stream data
processing and integration
•
Data analytics
and new machine learning theories
and models
•
Knowledge
discovery from multiple information
sources
•
Statistical,
mathematical and probabilistic
modeling and theories
•
Information
visualization and visual data
analytics
•
Information
retrieval and personalized
recommendation
•
Data provenanceand
graph analytics
•
Parallel and
distributed data storage and
processing infrastructure
•
MapReduce,
Hadoop, Spark, scalable computing
and storage platforms
•
Security,
privacy and data integrity in data
sharing, publishing and analysis
•
Big Data, data
science and cloud computing
•
Innovative
applications in business, finance,
industry and government cases
B. Data
Intensive Systems
Topics of particular interest
include, but are not limited to:
• Data-intensive applications and
their challenges
•
Scalable
computing platform such as Hadoop
and Spark
• Storage and
file systems
• High
performance data access toolkits
• Fault
tolerance, reliability, and
availability
• Meta-data
management
• Remote data
access
• Programming
models, abstractions for data
intensive computing
• Compiler and
runtime support
• Data
capturing, management, and
scheduling techniques
• Future
research challenges of data
intensive systems
• Performance
optimization techniques
• Replication,
archiving, preservation strategies
• Real-time
data intensive
systems
• Network
support for data intensive
systems
• Challenges
and solutions in the era of
multi/many-core platforms
• Stream
data
computing
• Green (Power
efficient) data intensive
systems
• Security and
protection of sensitive data in
collaborativeenvironments
• Data
intensive computing on accelerators
and GPUs
•
HPC system
architecture, programming models and
run-time systems for data intensive
applications
•
Productivity
tools, performance measuring and
benchmark for data intensive systems
•
Big Data, cloud
computing and data intensive systems
•
Innovative data
intensive applications such as big
sensing/surveillance/transport data,
big document/accounting data, big
online transaction data analysis and
etc.
Submission Guidelines
Submissions must include an
abstract, keywords, the e-mail
address of the corresponding author
and should not exceed 8 pages for
main conference, including tables
and figures in IEEE CS format. The
template files for LATEX or WORD can
be downloaded
here. All paper submissions must
represent original and unpublished
work. Each submission will be peer
reviewed by at least three program
committee members. Submission of a
paper should be regarded as an
undertaking that, should the paper
be accepted, at least one of the
authors will register for the
conference and present the work.
Submit your paper(s) in PDF file at
the submission site:
http://www.swinflow.org/confs/dsdis2015/submission.htm.
Publications
Accepted and presented papers will
be included into the IEEE Conference
Proceedings published by IEEE CS
Press. Authors of accepted papers,
or at least one of them, are
requested to register and present
their work at the conference,
otherwise their papers may be
removed from the digital libraries
of IEEE CS after
the conference.
Distinguished papers presented at
the conference, after further
revision, will be published in
special issues of Concurrency and
Computation: Practice and
Experience,
Journal of Network and Computer
Applications, Journal of
Computer and System Sciences
and IEEE Transactions on Big Data.