Demo Data from EDBT 2026 / reviewers in the wild / expert
Mike Baldwin
dblp:64/1346
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Environmental and earth informatics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
scientific visualization |
0.1 | 1 | 2006 | An Atmospheric Visual Analysis and Exploration System · IEEE Trans. Vis. Comput. Graph. 2006 |
Visualization and visual analytics › visual analytics
visual analysis |
0.1 | 1 | 2006 | An Atmospheric Visual Analysis and Exploration System · IEEE Trans. Vis. Comput. Graph. 2006 |
Environmental and earth informatics › meteorology
meteorological analysis |
0.0 | 1 | 2006 | An Atmospheric Visual Analysis and Exploration System · IEEE Trans. Vis. Comput. Graph. 2006 |
Methods — techniques the papers use, named apart from their topics
volume rendering · 0.1particle rendering · 0.1isosurface rendering · 0.1iso-surface rendering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | An Atmospheric Visual Analysis and Exploration SystemabstractMeteorological research involves the analysis of multi-field, multi-scale, and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. Unfortunately, traditional atmospheric visualization systems only provide tools to view a limited number of variables and small segments of the data. These tools are often restricted to two-dimensional contour or vector plots or three-dimensional isosurfaces. The meteorologist must mentally synthesize the data from multiple plots to glean the information needed to produce a coherent picture of the weather phenomenon of interest. In order to provide better tools to meteorologists and reduce system limitations, we have designed an integrated atmospheric visual analysis and exploration system for interactive analysis of weather data sets. Our system allows for the integrated visualization of 1D, 2D, and 3D atmospheric data sets in common meteorological grid structures and utilizes a variety of rendering techniques. These tools provide meteorologists with new abilities to analyze their data and answer questions on regions of interest, ranging from physics-based atmospheric rendering to illustrative rendering containing particles and glyphs. In this paper, we will discuss the use and performance of our visual analysis for two important meteorological applications. The first application is warm rain formation in small cumulus clouds. Here, our three-dimensional, interactive visualization of modeled drop trajectories within spatially correlated fields from a cloud simulation has provided researchers with new insight. Our second application is improving and validating severe storm models, specifically the Weather Research and Forecasting (WRF) model. This is done through correlative visualization of WRF model and experimental Doppler storm data. Yuyan Song, Nikolai A. Svakhine, Sonia Lasher-Trapp, Mike Baldwin, David S. Ebert |
IEEE Trans. Vis. Comput. Graph. | 5 |