Journal of Big Data is now indexed in the Science Citation Index Expanded (SCIE). We are happy to announce that in June 2022, we received our first Impact Factor rating of 10.835!
Journal News
Call for papers: Applications and development in Linked Open Data (LOD) cloud
This special issue proposal intends to capture the state-of-the-art applications and technologies such as the semantic web, machine learning, deep learning, natural language processing, internet of things, knowledge graph, process mining, and artificial intelligence, etc. which encompasses the wider spectrum of the Linked Open Data (LOD).
Call for papers: Advanced bio-inspired deep learning algorithms for multi-modal perceptual big data analysis in car-driver assistance systems
Next generation cars collect a wide variety of data coming from different systems that need to be processed and merged in order to provide adequate car driving assistance. The thematic series will look at approaches to car-driver assistance systems that make use of sophisticated bio-inspired algorithms and modern deep learning approaches.
Articles
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Human behavior in image-based Road Health Inspection Systems despite the emerging AutoML
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An efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis
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Machine learning approach for predicting production delays: a quarry company case study
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Estimating the carbon content of oceans using satellite sensor data
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A survey on Image Data Augmentation for Deep Learning
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Big data in healthcare: management, analysis and future prospects
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Deep learning applications and challenges in big data analytics
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Short-term stock market price trend prediction using a comprehensive deep learning system
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Sentiment analysis using product review data
Aims and scope
The Journal of Big Data publishes open-access original research on data science and data analytics. Deep learning algorithms and all applications of big data are welcomed. Survey papers and case studies are also considered.
The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.
The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.
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Annual Journal Metrics
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Citation Impact
10.835 - 2 Year Impact Factor (2021)
4.661 - Source Normalized Impact per Paper (SNIP)
2.592 - SCImago Journal Rank (SJR)
14.4 - CiteScoreSpeed
48 days to first decision for all manuscripts (Median)
116 days to first decision for reviewed manuscripts only (Median)Usage
1,878,037 downloads (2021)
982 Altmetric mentions (2021)
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- ISSN: 2196-1115 (electronic)