Frontiers reaches 6.4 on Journal Impact Factors
Big Data is dedicated to publishing novel results in large-scale data science and systems, related to Information and Computer Technology. The section welcomes submissions concerning methods, applications, infrastructure, and technical aspects of policy within this scope.
Methods cover the formulation, analysis and evaluation of statistical, mathematical, algorithmic, and computational approaches to big data. Specific approaches include sampling, sketching, compression, inference, and machine learning.
Applications broadly cover data acquisition, data management, data analysis and knowledge discovery, and the representation of big data arising from ICT systems. Topics include recommender systems, rule and pattern mining, natural language processing, anomaly detection and feature selection. Application settings include science and engineering, communication networks and services, government, utilities, health services, built environment, and the business and financial sectors.
Infrastructure includes sensing and communications systems for big data, architectures for massive computational and storage platforms, application software for distributed collection and analysis of big data, and systems to visualize and interact with big data and its analysis products. The section welcomes submissions that report informative experiences in implementation and deployment of big data systems.
Technical aspects of policy include data security and data privacy, and their role in addressing social, legal and ethical concerns arising from the use of big data.
To help disseminate research results and support the comparison of competitive approaches, we strongly encourage authors to make the products of their research, such as algorithms and working implementations, freely available for others to use. We also encourage authors to make available any datasets used in their research or to report applications of their research to publicly available datasets, where appropriate.
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Big Data welcomes submissions of the following article types: Book Review, Code, Correction, Data Report, Editorial, General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Policy and Practice Reviews, Review, Specialty Grand Challenge and Technology Report.
All manuscripts must be submitted directly to the section Big Data, where they are peer-reviewed by the Associate and Review Editors of the specialty section.
Articles published in the section Big Data will benefit from the Frontiers impact and tiering system after online publication. Authors of published original research with the highest impact, as judged democratically by the readers, will be invited by the Chief Editor to write a Frontiers Focused Review - a tier-climbing article. This is referred to as "democratic tiering". The author selection is based on article impact analytics of original research published in all Frontiers specialty journals and sections. Focused Reviews are centered on the original discovery, place it into a broader context, and aim to address the wider community across all of ICT and Digital Humanities.