primary topic: MetOceanVis: a visual analytics system for interactive exploration and extreme value analysis of multidimensional MetOcean data
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HTML Summary of #20680 MetOceanVis: a visual analytics system for interactive exploration and extreme value analysis of multidimensional MetOcean data
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primary topic: MetOceanVis: a visual analytics system for interactive exploration and extreme value analysis of multidimensional MetOcean data

MetOceanVis: a visual analytics system for interactive exploration and extreme value analysis of multidimensional MetOcean data
abstract: Analysing multidimensional meteorological and oceanographic (MetOcean) datasets across space and time remains challenging due to data volume, structural heterogeneity, and the need to coordinate exploratory analysis with statistical characterization of extreme events. In practice, visualization, exploratory data analysis, and extreme value analysis (EVA) are often performed using loosely coupled tools, limiting analytical coherence when spatial, temporal, or variable constraints change. This paper presents MetOceanVis, a modular web-based visual analytics system designed to support a coordinated, constraint-driven analytical workflow for spatio-temporal MetOcean data. The system adopts a four-layer architecture encompassing data ingestion, processing, integrated analytics, and interaction, enabling user-driven querying over temporal windows, spatial domains, and selected variables. Exploratory data analysis (EDA) views including time series plots, boxplots, scatter plots, correlation heatmaps, and histograms are integrated with EVA modules implementing block maxima and peak-over-threshold models, allowing extreme value characteristics to be explored within their spatial and statistical context. The system is demonstrated through a case study using the SEAFINE-2 dataset, focusing on extreme event-oriented analysis of MetOcean conditions in the South China Sea. A performance evaluation shows that the system maintains interactive responsiveness at the data scales considered in this work, supporting exploratory and extreme value analysis under varying query constraints. Â© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.
author list: authors
issue: 1
status: peerReviewed
status: published
volume: 22
date: 2026
is part of: repository
is part of: International Journal of Data Science and Analytics
type: AcademicArticle
type: Article
type: ArticleEPrint
type: EPrint

Springer Science and Business Media Deutschland GmbH
type: Organization

Azlan Ismail
family name: Ismail
given name: Azlan
type: Person

Nor Farisha M. Krishnan
family name: Krishnan
given name: Nor Farisha M.
type: Person

Faris Haziq Sazali
family name: Sazali
given name: Faris Haziq
type: Person

Jasni Mohamad Zain
family name: Mohamad Zain
given name: Jasni
type: Person

Jafreezal Jaafar
family name: Jaafar
given name: Jafreezal
type: Person

Farahida Hanim Mausor
family name: Mausor
given name: Farahida Hanim
type: Person

Mohd Hilmi Hasan
family name: Hasan
given name: Mohd Hilmi
type: Person

Siti Nuraishah Agos Jawaddi
family name: Jawaddi
given name: Siti Nuraishah Agos
type: Person

Nazleeni Samiha Haron
family name: Haron
given name: Nazleeni Samiha
type: Person

Izzatdin Abdul Aziz
family name: Aziz
given name: Izzatdin Abdul
type: Person

International Journal of Data Science and Analytics
issn: 2364415X
type: Collection