Visualisation strategies for environmental modelling data

Rink, Karsten; Bilke, Lars; Kolditz, Olaf

doi:10.1007/s12665-013-2970-2

Cited by 36 publications

(24 citation statements)

References 28 publications

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“…According to requirement B, it is necessary to provide data integration methods to transform input data into a format readable by the visualization application. We used open source tools like NCO and the OpenGeoSys (OGS) Data Explorer [ 9 , 40 ] (cf. Helbig et al 2014 [ 30 ]) for this preprocessing step (see Fig 2 ).…”

Section: Workflow and Applicationmentioning

confidence: 99%

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

et al. 2015

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BackgroundTo achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work.Methods and ResultsInstead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results.

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Section: Workflow and Applicationmentioning

confidence: 99%

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

et al. 2015

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“…The tests have been implemented by using the Unity3D visualization engine, 64 which has been previously used for DV purposes. [65][66][67][68][69][70][71] Finally, before starting the tests, the importance of carefully reading the navigation controls was also emphasized.…”

Section: Definition Of the Visual Testsmentioning

confidence: 99%

New insights into the suitability of the third dimension for visualizing multivariate/multidimensional data: A study based on loss of quality quantification

Gracia

González

Robles

et al. 2014

Information Visualization

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Most visualization techniques have traditionally used two-dimensional, instead of three-dimensional representations to visualize multidimensional and multivariate data. In this article, a way to demonstrate the underlying superiority of three-dimensional, with respect to two-dimensional, representation is proposed. Specifically, it is based on the inevitable quality degradation produced when reducing the data dimensionality. The problem is tackled from two different approaches: a visual and an analytical approach. First, a set of statistical tests (point classification, distance perception, and outlier identification) using the two-dimensional and three-dimensional visualization are carried out on a group of 40 users. The results indicate that there is an improvement in the accuracy introduced by the inclusion of a third dimension; however, these results do not allow to obtain definitive conclusions on the superiority of three-dimensional representation. Therefore, in order to draw further conclusions, a deeper study based on an analytical approach is proposed. The aim is to quantify the real loss of quality produced when the data are visualized in two-dimensional and three-dimensional spaces, in relation to the original data dimensionality, to analyze the difference between them. To achieve this, a recently proposed methodology is used. The results obtained by the analytical approach reported that the loss of quality reaches significantly high values only when switching from three-dimensional to two-dimensional representation. The considerable quality degradation suffered in the two-dimensional visualization strongly suggests the suitability of the third dimension to visualize data.

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“…These metadata are evaluated when loading the data sets into Unity and can be queried, e.g., for displaying the timestepping information as a text overlay. Multiple data sets can be arranged both in a spatial and in a temporal context and a variety of presentation techniques (e.g., defining camera animations, fading in/out of data sets, selection of subsets, displaying additional information) are implemented, see Rink et al (2014) for details.…”

Section: Workflowsmentioning

confidence: 99%

TESSIN VISLab—laboratory for scientific visualization

et al. 2014

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Scientific visualization is an integral part of the modeling workflow, enabling researchers to understand complex or large data sets and simulation results. A highresolution stereoscopic virtual reality (VR) environment further enhances the possibilities of visualization. Such an environment also allows collaboration in work groups including people of different backgrounds and to present results of research projects to stakeholders or the public. The requirements for the computing equipment driving the VR environment demand specialized software applications which can be run in a parallel fashion on a set of interconnected machines. Another challenge is to devise a useful data workflow from source data sets onto the display system. Therefore, we develop software applications like the OpenGeoSys Data Explorer, custom data conversion tools for established visualization packages such as ParaView and Visualization Toolkit as well as presentation and interaction techniques for 3D applications like Unity. We demonstrate our workflow by presenting visualization results for case studies from a broad range of applications. An outlook on how visualization techniques can be deeply integrated into the simulation process is given and future technical improvements such as a simplified hardware setup are outlined.

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Visualisation strategies for environmental modelling data

Cited by 36 publications

References 28 publications

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

New insights into the suitability of the third dimension for visualizing multivariate/multidimensional data: A study based on loss of quality quantification

TESSIN VISLab—laboratory for scientific visualization

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