Editorial Article

Editorial Statement of Intent

Chia-Lin Chang 1, Michael McAleer 2,*, Wing Keung Wong 3
1National Chung Hsing University, Taiwan
2National Tsing Hua University, Taiwan
3Asia University, Taiwan

*Corresponding author:

Michael McAleer, National Tsing Hua University, Taiwan, Email:

Journal Big Data and Computational Science (JBDCS) is a recently established open access peer reviewed multi-disciplinary journal for cognate disciplines in the Sciences and Social Sciences that will be inaugurated in 2018.

The journal focuses on disseminating the latest innovative theoretical and applied research in the analysis of big data using advanced and innovative computational science analytics and techniques, as well as their relationships to cognate disciplines across a wide range of areas in the Sciences and Social Sciences.

The intention of JBDCS is to publish innovative and high quality theoretical and applied papers, including case studies, on a wide range of topics in the analysis of big data and the use of advanced and innovative techniques in the mathematical and computational and sciences that are directly relevant for academics, researchers, and practitioners alike.

Advances in the various fields of informatics across a wide range of cognate disciplines are driving a major expansion in big data analytics and innovative developments in computational science.

Much of the innovative and advanced research on big data has focused on the application of advanced computational science methods for a better understanding of models and their underlying stochastic processes.

JBDCS seeks academically rigorous papers that will appeal to theoreticians and also have direct relevance to practitioners across a wide range of cognate disciplines in the Sciences and Social Sciences.

Papers that use rigorous mathematical, statistical and computational methods in the empirical testing of theory and models across a wide range of cognate disciplines are strongly encouraged.

In addition, case studies that encourage portability of the discoveries in empirical research to other studies and disciplines in the Sciences and Social Sciences are welcome.

JBDCS intends to coalesce researchers, academics, scientists, professors, advanced students, practitioners, and other interested individuals an opportunity to be well informed of the latest innovations in the analysis of big data through developments in computational science.

JBDCS encompasses a wide spectrum of innovative topics in the fields of Big Data and Computational Sciences, and cognate disciplines that include, but are not limited to:
(i) Big Data Analytics
(ii) Computational Science
(iii) Computer Simulations
(iv) Computational Modelling
(v) Informatics
(vi) Bioengineering
(vii) Molecular Engineering
(viii) Bioimaging Modulations
(ix) Proteomics
(x) Genomics
(xi) Machine Learning
(xii) Algorithms
(xiii) Molecular Medicine
(xiv) Imaging Informatics
(xv) Economics
(xvi) Finance
(xvii) Management
(xviii) Management Science
(xix) Marketing
(xx) Accounting Research
(xxi) Quantitative Methods
(xxii) Time Series Analysis
(xxiii) Cross Section Data Analysis
(xxiv) Dynamic Panel Data Models
(xxv) Statistics
(xxvi) Mathematics
(xxvii) Operations Research
(xxviii) Engineering.

The intention of JBDCS is to publish articles that are connected to, but are not limited by, the following:
(1) Computational Science
(2) Computer Programming
(3) Big Data Analytics
(4) Simulations
(5) Numerical Analysis
(6) Theoretical and Applied Mathematics
(7) Theoretical and Applied Statistics
(8) Theoretical and AppliedEconometrics
(9) Environmental Science
(10) Fossil Fuels
(11) Carbon Emissions
(12) Climate Change and Global Warming
(13) Environmental Management
(14) Financial Decision Making
(15) Financial Risk Analysis
(16) Financial Risk Management
(17) Economics
(18) Finance
(19) Financial Econometrics
(20) Forecasting
(21) Energy Economics
(22) Energy Finance
(23) Renewable and Sustainable Energy
(24) Green Energy
(25) Agricultural Commodities
(26) Management
(27) Management Science
(28) Marketing
(29) Operations Research
(30) Engineering
(31) Financial Engineering
(32) Bioengineering
(33) Big Data Analytics
(34) Data Mining
(35) Informatics
(36) Imaging Informatics
(37) Molecular Engineering
(38) Docking simulations
(39) Bioimaging and modulations
(40) Proteomics
(41) Genomics

JBDCS invites authors to submit manuscripts to be considered for inclusion in Volume 1(1), as well as in future volumes and issues.

The journal adheres to a stringent double blind review policy to maintain publication quality.

The journal encourages recent discoveries and innovations comprising theoretical, conceptual and empirical research in Big Data, Computational Science, and cognate disciplines in the Sciences and Social Sciences.

For further information about submitting a manuscript for possible publication, please contact: jbd.cs@clytoaccess.com

JBDCS has a distinguished International Advisory Board, comprising leading academics from leading international institutions.

The Editorial Board of JBDCS exercises control over the editorial content of the journal, which is intended to be published on a quarterly basis.

JBDCS seeks to expand membership of the International Advisory Board, and welcomes a wide range of members of the Editorial Board and editorial reviewing panels.

For further information about joining the Editorial Board and Editorial Reviewing Panels, please contact: jbd.cs@clytoaccess.com

The journal’s mission is to expand the horizon of the academic disciplines of Big Data and Computational Sciences through a broad dissemination of innovations and knowledge sharing to expand understanding of these issues in cognate disciplines in the Sciences and Social Sciences.

It is a genuine challenge, and an honour and pleasure for the three co-editorialists to have been appointed the Co-Editor-in-Chief, Editor-in-Chief, and Co-Editor-in-Chief, respectively, of the Journal of Big Data and Computational Science (JBDCS).

We look forward to working with the active and vibrant members of the International Advisory Board, Editorial Board, extensive reviewing panels, and contributors to make JBDCS an accessible and leading outlet for high quality academic, theoretical, and practical research in all areas of big data and computational science, and their relationships to cognate disciplines in the Sciences and Social Sciences.

For financial support, the authors wish to thank the National Science Council, Ministry of Science and Technology (MOST), Taiwan, and the Australian Research Council.

Published: 18 October 2017

Copyright:

© 2017 Chang et al.. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.