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<export-example>
  <doc>
    <id>1191</id>
    <completedYear>2010</completedYear>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2010-12-20</completedDate>
    <publishedDate>2010-12-20</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Visual Approach to Analysis of Stress Tensor Fields</title>
    <abstract language="eng">We present a visual approach for the exploration of stress tensor fields. Therefore, we introduce the idea of multiple linked views to tensor visualization. In contrast to common tensor visualization methods that only provide a single view to the tensor field, we pursue the idea of providing various perspectives onto the data in attribute and object space. Especially in the context of stress tensors, advanced tensor visualization methods have a young tradition. Thus, we propose a combination of visualization techniques domain experts are used to with statistical views of tensor attributes. The application of this concept to tensor fields was achieved by extending the notion of shape space. It provides an intuitive way of finding tensor invariants that represent relevant physical properties. Using brushing techniques, the user can select features in attribute space, which are mapped to displayable entities in a three-dimensional hybrid visualization in object space. Volume rendering serves as context, while glyphs encode the whole tensor information in focus regions. Tensorlines can be included to emphasize directionally coherent features in the tensor field. We show that the benefit of such a multi-perspective approach is manifold. Foremost, it provides easy access to the complexity of tensor data. Moreover, including wellknown analysis tools, such as Mohr diagrams, users can familiarize themselves gradually with novel visualization methods. Finally, by employing a focus-driven hybrid rendering, we significantly reduce clutter, which was a major problem of other three-dimensional tensor visualization methods.</abstract>
    <identifier type="serial">10-26</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-11915</identifier>
    <identifier type="doi">/10.4230/DFU.Vol2.SciViz.2011.188</identifier>
    <enrichment key="SourceTitle">Appeared in: Scientific Visualization: Interactions, Features, Metaphors, Dagstuhl Follow-Ups, 2, 2011, pp. 188-211</enrichment>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Andrea Kratz</author>
    <submitter>-empty- (Opus4 user: admin)</submitter>
    <author>Björn Meyer</author>
    <submitter>Andrea Kratz</submitter>
    <author>Ingrid Hotz</author>
    <series>
      <title>ZIB-Report</title>
      <number>10-26</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Visualisierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datenanalyse</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Tensorfelder</value>
    </subject>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="persons" number="kratz">Kratz, Andrea</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1191/ZR-10-26.pdf</file>
  </doc>
  <doc>
    <id>3712</id>
    <completedYear>2010</completedYear>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1003</pageFirst>
    <pageLast>1012</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>29</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Effective Techniques to Visualize Filament-Surface Relationships</title>
    <parentTitle language="eng">Comput. Graph. Forum</parentTitle>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="FulltextUrl">http://www.zib.de/visual-publications/sources/src-2010/Kuss_EuroVis2010.pdf</enrichment>
    <author>Anja Kuß</author>
    <author>Maria Gensel</author>
    <author>Björn Meyer</author>
    <author>Vincent J. Dercksen</author>
    <author>Steffen Prohaska</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="visalgo">Visual Data Analysis in Science and Engineering</collection>
    <collection role="institutes" number="vissys">Image Analysis in Biology and Materials Science</collection>
    <collection role="persons" number="prohaska">Prohaska, Steffen</collection>
    <collection role="projects" number="Neuro">Neuro</collection>
    <collection role="projects" number="DIGINEURO">DIGINEURO</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3677</id>
    <completedYear>2011</completedYear>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>188</pageFirst>
    <pageLast>211</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>2</volume>
    <type>incollection</type>
    <publisherName>Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik</publisherName>
    <publisherPlace>Dagstuhl, Germany</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Visual Approach to Analysis of Stress Tensor Fields</title>
    <parentTitle language="eng">Scientific Visualization: Interactions, Features, Metaphors</parentTitle>
    <identifier type="doi">10.4230/DFU.Vol2.SciViz.2011.188</identifier>
    <identifier type="url">http://drops.dagstuhl.de/opus/volltexte/2011/3296</identifier>
    <enrichment key="Series">Dagstuhl Follow-Ups</enrichment>
    <enrichment key="PreprintUrn">nbn:de:0297-zib-11915</enrichment>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Andrea Kratz</author>
    <editor>Hans Hagen</editor>
    <author>Björn Meyer</author>
    <author>Ingrid Hotz</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="compvis">Vergleichende Visualisierung</collection>
    <collection role="persons" number="kratz">Kratz, Andrea</collection>
    <collection role="projects" number="TENSOR-VIS">TENSOR-VIS</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3760</id>
    <completedYear>2008</completedYear>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>177</pageFirst>
    <pageLast>184</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Ontology-Based Visualization of Hierarchical Neuroanatomical Structures</title>
    <parentTitle language="eng">Proceedings of the Eurographics Workshop on Visual Computing for Biomedicine VCBM 2008</parentTitle>
    <author>Anja Kuß</author>
    <author>Steffen Prohaska</author>
    <author>Björn Meyer</author>
    <author>Jürgen Rybak</author>
    <author>Hans-Christian Hege</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="visalgo">Visual Data Analysis in Science and Engineering</collection>
    <collection role="institutes" number="vissys">Image Analysis in Biology and Materials Science</collection>
    <collection role="persons" number="hege">Hege, Hans-Christian</collection>
    <collection role="persons" number="prohaska">Prohaska, Steffen</collection>
    <collection role="projects" number="DIGINEURO">DIGINEURO</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>6270</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>69</pageFirst>
    <pageLast>100</pageLast>
    <pageNumber/>
    <edition/>
    <issue>702</issue>
    <volume>143</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Large-eddy simulations over Germany using ICON: a comprehensive evaluation</title>
    <abstract language="eng">Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.</abstract>
    <parentTitle language="eng">Quarterly Journal of the Royal Meteorological Society</parentTitle>
    <identifier type="doi">10.1002/qj.2947</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Rieke Heinze</author>
    <submitter>Hans-Christian Hege</submitter>
    <author>Anurag Dipankar</author>
    <author>Cintia Carbajal Henken</author>
    <author>Christopher Moseley</author>
    <author>Odran Sourdeval</author>
    <author>Silke Trömel</author>
    <author>Xinxin Xie</author>
    <author>Panos Adamidis</author>
    <author>Felix Ament</author>
    <author>Holger Baars</author>
    <author>Christian Barthlott</author>
    <author>Andreas Behrendt</author>
    <author>Ulrich Blahak</author>
    <author>Sebastian Bley</author>
    <author>Slavko Brdar</author>
    <author>Matthias Brueck</author>
    <author>Susanne Crewell</author>
    <author>Hartwig Deneke</author>
    <author>Paolo Di Girolamo</author>
    <author>Raquel Evaristo</author>
    <author>Jürgen Fischer</author>
    <author>Christopher Frank</author>
    <author>Petra Friederichs</author>
    <author>Tobias Göcke</author>
    <author>Ksenia Gorges</author>
    <author>Luke Hande</author>
    <author>Moritz Hanke</author>
    <author>Akio Hansen</author>
    <author>Hans-Christian Hege</author>
    <author>Corinna Hose</author>
    <author>Thomas Jahns</author>
    <author>Norbert Kalthoff</author>
    <author>Daniel Klocke</author>
    <author>Stefan Kneifel</author>
    <author>Peter Knippertz</author>
    <author>Alexander Kuhn</author>
    <author>Thriza van Laar</author>
    <author>Andreas Macke</author>
    <author>Vera Maurer</author>
    <author>Bernhard Mayer</author>
    <author>Catrin I. Meyer</author>
    <author>Shravan K. Muppa</author>
    <author>Roeland A. J. Neggers</author>
    <author>Emiliano Orlandi</author>
    <author>Florian Pantillon</author>
    <author>Bernhard Pospichal</author>
    <author>Niklas Röber</author>
    <author>Leonhard Scheck</author>
    <author>Axel Seifert</author>
    <author>Patric Seifert</author>
    <author>Fabian Senf</author>
    <author>Pavan Siligam</author>
    <author>Clemens Simmer</author>
    <author>Sandra Steinke</author>
    <author>Bjorn Stevens</author>
    <author>Kathrin Wapler</author>
    <author>Michael Weniger</author>
    <author>Volker Wulfmeyer</author>
    <author>Günther Zängl</author>
    <author>Dan Zhang</author>
    <author>Johannes Quaas</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="visalgo">Visual Data Analysis in Science and Engineering</collection>
    <collection role="persons" number="hege">Hege, Hans-Christian</collection>
    <collection role="projects" number="HD(CP)2">HD(CP)2</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
</export-example>
