Special Issues
Table of Content

Big Data Technologies and Applications for a Data-Driven World

Submission Deadline: 31 March 2026 View: 358 Submit to Special Issue

Guest Editors

Assist. Prof. Carlos Fernandez-Basso

Email: cjferba@decsai.ugr.es

Affiliation: Department of Computer Science and Artificial Intelligence, University of Granada, Granada 18071, Spain

Homepage:

Research Interests: big data analytics, distributed systems, machine learning, data engineering, smart cities, artificial intelligence in health

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Assoc. Prof. Karel Gutiérrez-Batista

Email: karel@decsai.ugr.es

Affiliation: Department of Computer Science and Artificial Intelligence, University of Granada, Granada 18071, Spain

Homepage:

Research Interests: natural language processing, multidimensional systems, machine learning, deep learning, knowledge graph, social networks analysis


Summary

The exponential growth of data across various sectors has revolutionized decision-making processes, service delivery, and knowledge generation. This Special Issue on Big Data Applications in the Real World aims to compile impactful contributions demonstrating the practical application of big data technologies to address concrete challenges in diverse domains.

The issue seeks to highlight innovative methods, architectures, and case studies where big data has been instrumental in driving transformation in sectors such as health, education, governance, smart cities, and industry. Both theoretical and applied works are welcome, with a focus on practical impact and reproducibility.

Suggested themes:
· Real-time Big Data Systems for Smart Cities
· Big Data in Public Health and Epidemic Control
· Scalable Data Platforms for Industry 4.0
· Big Data Applications in Sustainable Development
· Data-Driven Decision Making in Government
· Machine Learning Pipelines on Large-Scale Data
· Privacy-Preserving Big Data Architectures


Keywords

Big Data, Real-World Applications, Smart Cities, Scalable Data Systems, Data Governance, Data Analytics, Industry 4.0, Urban Computing, Distributed Computing, Data Engineering

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