IEEE Computational Intelligence Magazine - August 2020 - 9

Society
Briefs

Longbing Cao
IEEE TF-DSAA Chair, University of
Technology Sydney, AUSTRALIA
Marley M.B.R. Vellasco
IEEE CIS VP-Conferences, Pontifical
Catholic University of Rio de Janeiro
(PUC-Rio), BRAZIL

IEEE DSAA-The IEEE Flagship Conference in Data Science
The Era of Data Science and
Analytics

he twenty-first century has ushered in a new age that is coined as
data science and big data analytics.
Data-driven scientific discovery is regarded as the fourth science paradigm. Data
science has been a core driver of the
new-generation science, technologies and
economy, and is driving new researches,
innovation, profession, applications and
education across both disciplines and
business domains. There are many scientific and technical challenges associated
with big data, ranging from data capture,
creation, storage, search, sharing, modeling, representation, analysis, learning,
visualization, explanation, and decisionmaking. Among the many data characteristics and complexities to be addressed,
we mention here the hybridization of
heterogeneous, multisource, hierarchical,
interactive, dynamic, multidimensional,
and quality-poor data mixed with realtime business operations, strategic planning,
decision-making, value creation, and
future developments. Another important
agenda in the data science community is
to address the misinformation and pitfalls
and promote a deep understanding of the
data science nature and reality.
Accordingly, the field of data sciences
and big data analytics have been evolving
from statistics since half century ago to
broad areas including but not limited
to data and signal analytics, knowledge discovery, information retrieval,
Digital Object Identifier 10.1109/MCI.2020.2998229
Date of current version: 15 July 2020

machine learning, statistics, optimization,
computing, and data management. By
synergizing the three big areas-statistics, informatics and computing, data
science has been spreading to essential
and specific areas such as (1) data intelligence and complexity analysis, (2) representation, modeling, analytics, mining
and learning including statistical and deep
learning, (3) computational intelligence
including neural networks, evolutionary
computing, fuzzy systems, (4) neuroscience and linguistics, (5) behavioral science
and social and economic computing, (6)
uncertainty and optimization, (7) system and modeling infrastructures and
architectures, (8) networking and interoperation, (9) social issues including
privacy, security, trust, value and impact,
(10) enterprises, services, applications,
solutions and systems, and (11) simulation,
visualization and explanation.
IEEE DSAA-Transdisciplinary
Data Science Led by IEEE

The IEEE International Conference on
Data Science and Advanced Analytics
(IEEE DSAA) (see more about DSAA at
dsaa2020.dsaa.co) aims to be a premier
forum for addressing the above ever
increasing and important demand, data
volume and complexities, and the associated business problems, opportunities,
decisions and values in a translational and
transdisciplinary approach. DSAA was
launched in 2014 in Shanghai chaired by
Prof. Masaru Kitsuregawa and Prof. Philip S Yu as a major IEEE initiative in data
science and big data, received support
from the IEEE Big Data Initiative. Since

2015, DSAA has been financially sponsored by the IEEE Computational Intelligence Society (CIS), and also technically
sponsored by ACM through SIGKDD,
the American Statistical Association
(ASA), and the China Computer Foundation (CCF). DSAA has been successfully rotated in Asia, Europe and America
with DSAA'2019 held in Washington
chaired by Prof. Philip S Yu and Prof.
Richard De Veaux, DSAA'2018 in Turin
chaired by Dr. Francesco Bonchi and
Prof. Foster Provost, DSAA'2017 in
Tokyo Chaired by Prof. Fosca Giannotti,
Prof.Tomoyuki Higuchi and Prof. Motoda Motoda, DSAA'2016 in Montreal
chaired by Prof. Stan Matwin and Prof.
Osmar R. Zaiane, DSAA'2015 in Paris
chaired by Prof. Longbing Cao and Prof.
Eric Gaussier. DSAA'2020 will be held in
Sydney on 6-9 Oct. 2020 and chaired by
Prof. Geoff Webb and Dr. Usama Fayyad.
IEEE DSAA, technically managed
by the IEEE CIS Task Force on Data
Science and Advanced Analytics (TFDSAA), has taken a strong transdisciplinary approach. The annual DSAA
provides a premier data science forum
that brings together researchers, industry
and government practitioners, as well as
developers and users in statistics, computing science, informatics and intelligence
science for the exchange of the latest theoretical developments in data science and
analytics and the best practice for a wide
range of applications. DSAA also features
its cross-domain interactions and gapbridging between academia and business
for innovative industry and government
data science and analytics.

AUGUST 2020 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE

http://dsaa2020.dsaa.co

IEEE Computational Intelligence Magazine - August 2020

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