Interactive visual analysis of families of curves using data aggregation and derivation

Konyha, Z.; Lež, Alan; Matković, Krešimir; Jelovic, Mario; Hauser, Helwig

doi:10.1145/2362456.2362487

Cited by 18 publications

(14 citation statements)

References 24 publications

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“…It is a suitable approach for a certain frame analysis, but it does not tackle spatio-temporal data. Follow-up studies such as the one by [14] looking into families of curves also provide methods for the analysis of non-spatial multi-run data.…”

Section: Related Workmentioning

confidence: 99%

A Top-Down Interactive Visual Analysis Approach for Physical Simulation Ensembles at Different Aggregation Levels

Fofonov

Linsen

2018

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Abstract:Physical simulations aim at modeling and computing spatio-temporal phenomena. As the simulations depend on initial conditions and/or parameter settings whose impact is to be investigated, a larger number of simulation runs is commonly executed. Analyzing all facets of such multi-run multi-field spatio-temporal simulation data poses a challenge for visualization. It requires the design of different visual encodings that aggregate information in multiple ways and at multiple abstraction levels. We present a top-down interactive visual analysis tool of multi-run data from physical simulations named MultiVisA that is based on plots at different aggregation levels. The most aggregated visual representation is a histogram-based plot that allows for the investigation of the distribution of function values within all simulation runs. When expanding over time, a density-based time-series plot allows for the detection of temporal patterns and outliers within the ensemble of multiple runs for single and multiple fields. Finally, not aggregating over runs in a similarity-based plot allows for the comparison of multiple or individual runs and their behavior over time. Coordinated views allow for linking the plots of the three aggregation levels to spatial visualizations in physical space. We apply MultiVisA to physical simulations from the field of climate research and astrophysics. We document the analysis process, demonstrate its effectiveness, and provide evaluations involving domain experts.

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Section: Related Workmentioning

confidence: 99%

A Top-Down Interactive Visual Analysis Approach for Physical Simulation Ensembles at Different Aggregation Levels

Fofonov

Linsen

2018

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“…They focus on the evaluation of the provided models, while we focus on the description of data relations by means of local regression models. We exploit on-the-fly data aggregation as described by Konyha et al [15].…”

Section: Related Workmentioning

confidence: 99%

“…Our approach makes such analysis tasks possible, combining the best from interactive and from automatic data analysis. Accordingly, there isn't any predefined set of attributes which would be valid for all data sets and all cases, but the interactive, on-demand derivation of such aggregates proves useful instead [15].…”

Section: Data Description and Problem Statementmentioning

confidence: 99%

Quantitative Externalization of Visual Data Analysis Results Using Local Regression Models

Matković

Abraham²,

Jelovic³

et al. 2017

Lecture Notes in Computer Science

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Both interactive visualization and computational analysis methods are useful for data studies and an integration of both approaches is promising to successfully combine the benefits of both methodologies. In interactive data exploration and analysis workflows, we need successful means to quantitatively externalize results from data studies, amounting to a particular challenge for the usually qualitative visual data analysis. In this paper, we propose a hybrid approach in order to quantitatively externalize valuable findings from interactive visual data exploration and analysis, based on local linear regression models. The models are built on user-selected subsets of the data, and we provide a way of keeping track of these models and comparing them. As an additional benefit, we also provide the user with the numeric model coefficients. Once the models are available, they can be used in subsequent steps of the workflow. A model-based optimization can then be performed, for example, or more complex models can be reconstructed using an inversion of the local models. We study two datasets to exemplify the proposed approach, a meteorological data set for illustration purposes and a simulation ensemble from the automotive industry as an actual case study.

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“…These plots are so specific that they do not appear in other tools. The newly developed Spinel Explorer supports iterative composite brushing and on-the-fly data derivation [16]. Some other tools, SimVis, for example, support a feature definition language [5] to create composite brushes.…”

Section: Interactive Visual Analysismentioning

confidence: 99%

The Spinel Explorer—Interactive Visual Analysis of Spinel Group Minerals

Ganuza

Ferracutti

Gargiulo

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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Geologists usually deal with rocks that are up to several thousand million years old. They try to reconstruct the tectonic settings where these rocks were formed and the history of events that affected them through the geological time. The spinel group minerals provide useful information regarding the geological environment in which the host rocks were formed. They constitute excellent indicators of geological environments (tectonic settings) and are of invaluable help in the search for mineral deposits of economic interest. The current workflow requires the scientists to work with different applications to analyze spine data. They do use specific diagrams, but these are usually not interactive. The current workflow hinders domain experts to fully exploit the potentials of tediously and expensively collected data. In this paper, we introduce the Spinel Explorer-an interactive visual analysis application for spinel group minerals. The design of the Spinel Explorer and of the newly introduced interactions is a result of a careful study of geologists' tasks. The Spinel Explorer includes most of the diagrams commonly used for analyzing spinel group minerals, including 2D binary plots, ternary plots, and 3D Spinel prism plots. Besides specific plots, conventional information visualization views are also integrated in the Spinel Explorer. All views are interactive and linked. The Spinel Explorer supports conventional statistics commonly used in spinel minerals exploration. The statistics views and different data derivation techniques are fully integrated in the system. Besides the Spinel Explorer as newly proposed interactive exploration system, we also describe the identified analysis tasks, and propose a new workflow. We evaluate the Spinel Explorer using real-life data from two locations in Argentina: the Frontal Cordillera in Central Andes and Patagonia. We describe the new findings of the geologists which would have been much more difficult to achieve using the current workflow only. Very positive feedback from geologists confirms the usefulness of the Spinel Explorer.

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Interactive visual analysis of families of curves using data aggregation and derivation

Cited by 18 publications

References 24 publications

A Top-Down Interactive Visual Analysis Approach for Physical Simulation Ensembles at Different Aggregation Levels

A Top-Down Interactive Visual Analysis Approach for Physical Simulation Ensembles at Different Aggregation Levels

Quantitative Externalization of Visual Data Analysis Results Using Local Regression Models

The Spinel Explorer—Interactive Visual Analysis of Spinel Group Minerals

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