[AISWorld] Applied Science (IF=2.838) SI "Advances in Data Science and Its Applications"

[Dr. Dickson K.W. CHIU]

Special Issue Editors
Dr. Dickson K.W. Chiu E-Mail
<https://www.mdpi.com/journal/applsci/special_issues/ZB22K14K1M> Website
<https://audio.edu.hku.hk/faculty-academics/dchiu88>
*Guest Editor (dicksonchiu at ieee.org <dicksonchiu at ieee.org>)*
Faculty of Education, The University of Hong Kong, Pokfulam, Hong Kong,
China
Interests: library and information management; service computing; e-learning
Prof. Dr. Kevin K.W. Ho E-Mail
<https://www.mdpi.com/journal/applsci/special_issues/ZB22K14K1M> Website
<https://www.mbaib.gsbs.tsukuba.ac.jp/facultyindex/kevinho/>
SciProfiles <https://sciprofiles.com/profile/2562872>

*Guest Editor*
Graduate School of Business Sciences, Humanities and Social Sciences,
University of Tsukuba, Tokyo, Japan
Interests: management information systems; information management;
management education; library management
Special Issue Information

Dear Colleagues,

Data science refers to the interdisciplinary application of scientific
methods and systems from which knowledge and insights can be obtained, from
structured or unstructured data sources, for application in various
domains. Data science typically involves data mining, machine learning,
statistics, data analysis, informatics, and Big Data applied across diverse
domains.

This Special Issue (SI) welcomes scientific, empirical, conceptual, and
methodological contributions on contemporary data science topics; these
should discuss applications in various non-commercial domains, including
healthcare, mobile lifestyles, learning, culture, digital transformation,
non-profit organizations, government, and non-government services. We also
aim to provide a forum for interdisciplinary and emerging data science
topics, including socio-data analytics, learning analytics, knowledge
management, Big Data, Blockchain technologies, and other data-driven
technology innovations. This Special Issue welcomes an array of approaches
and epistemologies, including qualitative, quantitative, and mixed-methods,
as well as established methodologies such as action, participatory,
evaluation, design, and development.

Topics of interest include, but are not limited to:

   - Big Data analytics.
   - Business and organizational analytics.
   - Socio-data analytics, bibliometrics, and linked data.
   - Learning analytics.
   - Intelligent analytics and knowledge discovery.
   - Blockchain analytics and applications.
   - Data-driven technology innovation and system design.
   - Digitalization for analytics.
   - Machine learning, neural networks, and deep learning.
   - Data science for the Internet of Things, Blockchain, the Cloud,
   service computing, and other emerging computing paradigms.
   - The adoption, diffusion, applications, innovations, management, and
   governance of data science.
   - Security, privacy, reliability, education, and development issues in
   data science.

Dr. Dickson K.W. Chiu
Prof. Dr. Kevin K.W. Ho
*Guest Editors*

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering
<https://www.mdpi.com/user/register/> and logging in to this website
<https://www.mdpi.com/user/login/>. Once you are registered, click here to
go to the submission form
<https://susy.mdpi.com/user/manuscripts/upload/?journal=applsci>.
Manuscripts can be submitted until the deadline. All submissions that pass
pre-check are peer-reviewed. Accepted papers will be published continuously
in the journal (as soon as accepted) and will be listed together on the
special issue website. Research articles, review articles as well as short
communications are invited. For planned papers, a title and short abstract
(about 100 words) can be sent to the Editorial Office for announcement on
this website.

Submitted manuscripts should not have been published previously, nor be
under consideration for publication elsewhere (except conference
proceedings papers). All manuscripts are thoroughly refereed through a
single-blind peer-review process. A guide for authors and other relevant
information for submission of manuscripts is available on the Instructions
for Authors <https://www.mdpi.com/journal/applsci/instructions> page. *Applied
Sciences* <https://www.mdpi.com/journal/applsci/> is an international
peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors
<https://www.mdpi.com/journal/applsci/instructions> page before submitting
a manuscript. The Article Processing Charge (APC)
<https://www.mdpi.com/about/apc/> for publication in this open access
<https://www.mdpi.com/about/openaccess/> journal is 2300 CHF (Swiss
Francs). Submitted papers should be well formatted and use good English.
Authors may use MDPI's English editing service
<https://www.mdpi.com/authors/english> prior to publication or during
author revisions.

Keywords

   - data science
   - data analytics
   - big data
   - learning analytics
   - business intelligence