Special Issue on Machine Learning Approaches in Big Data Visualization

Nikos Bikakis, Panos K. Chrysanthis, George Papastefanatos, Tobias Schreck

Research output: Contribution to journalEditorialpeer-review

Abstract

The articles in this special section focus on analytic rendering and hardware-accelerated simulation for scientific applications. Data visualization is now one of the cornerstones of data science, turning the abundance of big data being produced through modern systems into actionable knowledge. Data visualization in the big data era raises the need to co-design and more closely align the underlying data management systems with the user-oriented techniques that state-of-the-art visualization systems now offer. In addition, the tight integration of suitable machine learning approaches with data visualization and their control by users-in-theloop promises to enhance scalability, effectiveness, and adaptivity of the interactive visual data analysis process. This special issue attracted and publishes research work on multidisciplinary research areas from the human–computer interaction, computer graphics, and data management communities
Original languageEnglish
Pages (from-to)39-40
Number of pages2
JournalIEEE Computer Graphics and Applications
Volume42
Issue number3
DOIs
Publication statusPublished - 2022

Fields of Expertise

  • Information, Communication & Computing

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