Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …

Visualization and visual analysis play important roles in exploring, analyzing, and
presenting scientific data. In many disciplines, data and model scenarios are becoming …

This article surveys the history and current state of the art of visualization in meteorology,
focusing on visualization techniques and tools used for meteorological data analysis. We …

In many application fields, data analysts have to deal with datasets that contain many
expressions per item. The effective analysis of such multivariate datasets is dependent on …

This paper presents an efficient algorithm for the computation of the Reeb space of an input
bivariate piecewise linear scalar function f defined on a tetrahedral mesh. By extending and …

Information theory provides a theoretical framework for measuring information content for an
observed variable, and has attracted much attention from visualization researchers for its …

Datasets with a large number of dimensions per data item (hundreds or more) are
challenging both for computational and visual analysis. Moreover, these dimensions have …

Visualization is a key technology for analyzing and presenting climate simulations and
observations as well as related social and ecological data. Furthermore, mediating research …

Streamline seeding rakes are widely used in vector field visualization. We present new
approaches for calculating similarity between integral curves (streamlines and pathlines) …

Ever improving computing power and technological advances are greatly augmenting data
collection and scientific observation. This has directly contributed to increased data …