International Journal of Data Science and Analytics (ISSN: 2364-415X)

Description

Data-driven scientific discovery has been established as an important emerging paradigm driving research innovation and practical development in domains such as business, public sector, social science, the Internet of Things, and cloud computing. The field encompasses the larger areas of data analytics, machine learning, and managing and using big data, while related new scientific challenges range from data capture, creation, storage, search, sharing, analysis, and visualization, to integration across heterogeneous and interdependent complex resources and medias for real-time decision-making, collaboration, and, ultimately, value creation.
The International Journal of Data Science and Analytics aims to be a prestigious publishing venue in the data science and analytics field for exchanging new theoretical and experimental design, solid findings and insights, best practices and applications to real-life situations, and review about new opportunities and frameworks for data science and analytics.
Scope
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Topics of relevance include all aspects of the scientific foundations, techniques and applications of data and analytics, such as:
? new statistical and mathematical theories and techniques;
? data complexity and computational complexity theories and techniques;
? data characteristics understanding, and feature/variable and data distribution analysis;
? data and knowledge creation, discovery, processing, modelling, mapping, search, interoperability, exchange, integration, and visualization;
? machine learning, data mining, text analytics, and multimedia analytics;
? computational intelligence-based theories, methods and applications;
? complex database management, indexing, and query processing;
? information retrieval, recommendation and services;
? cloud computing, big data infrastructure and service-oriented computing;
? parallel computing and high performance computing, scalable computing and large-scale optimization;
? real-time analytics, in-memory computing, and in-database computing;
? ontological engineering and the Semantic Web;
? business analytics, corporate analytics, mobile analytics, network analytics, Web/online analytics and visual analytics;
? behaviour informatics, cultural computing, economic computing, financial analytics, governmental analytics, and social analytics/computing;
? bioinformatics, computational biology, health and medical analytics;
? cross-domain, cross-media and hybrid data, network and application integration and analysis;
? scientific analytical methodologies and workflows, and computational devices and services;
? new data processing and analytical languages, tools and systems;
? security, trust, risk, and privacy, ethical and legal issues;
? survey and review