Name
Title | ||
|---|---|---|
Visual Analytics for Comparison of Ocean Model Output with Reference Data: Detecting and Analyzing Geophysical Processes Using Clustering Ensembles |
Abstract | ||
|---|---|---|
Researchers assess the quality of an ocean model by comparing its output to that of a previous model version or to observations. One objective of the comparison is to detect and to analyze differences and similarities between both data sets regarding geophysical processes, such as particular ocean currents. This task involves the analysis of thousands or hundreds of thousands of geographically referenced temporal profiles in the data. To cope with the amount of data, modelers combine aggregation of temporal profiles to single statistical values with visual comparison. Although this strategy is based on experience and a well-grounded body of expert knowledge, our discussions with domain experts have shown that it has two limitations: (1) using a single statistical measure results in a rather limited scope of the comparison and in significant loss of information, and (2) the decisions modelers have to make in the process may lead to important aspects being overlooked. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TVCG.2014.2346751 | Visualization and Computer Graphics, IEEE Transactions |
Keywords | Field | DocType |
data analysis,expert systems,geophysics computing,graphical user interfaces,learning (artificial intelligence),ocean waves,pattern clustering,statistical analysis,tides,clustering algorithms,clustering ensembles,data set differences,data set similarities,decision modelling,domain experts,expert knowledge,geographically referenced temporal profiles,geophysical process analysis,geophysical process detection,geophysical process representation,geospatial distribution,information loss,ocean currents,ocean model output,ocean model quality,parameterizations,reference data,statistical measure,statistical values,subjectivity reduction,temporal behavior,temporal profile aggregation,temporal profile cluster detection,temporal profiles,visual analytics,visual comparison,visual interface,Ocean modeling,cluster ensembles,geospatial time,model assessment,series,visual analytics,visual comparison | Geospatial analysis,Reference data (financial markets),Data modeling,Data mining,Data set,Visual comparison,Computer science,Visualization,Visual analytics,Artificial intelligence,Cluster analysis,Machine learning | Journal |
Volume | Issue | ISSN |
20 | 12 | 1077-2626 |
Citations | PageRank | References |
7 | 0.48 | 22 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Köthur | 1 | 44 | 2.77 |
| Mike Sips | 2 | 381 | 25.43 |
| Henryk Dobslaw | 3 | 17 | 2.44 |
| Doris Dransch | 4 | 168 | 10.97 |