Advances in Data Science and Its Applications

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 and logging in to this website. Once you are registered, click here to go to the submission form. 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 250 words) can be sent to the Editorial Office for assessment.

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 page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.