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"title": "Interactive Exploded Views for Molecular Structures",
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"abstract": "We propose an approach to interactively create exploded views of molecular structures with the goal to help domain experts in their design process and provide them with a meaningful visual representation of component relationships. Exploded views are excellently suited to manage visual occlusion of structure components, which is one of the main challenges when visualizing complex 3D data. In this paper, we discuss four key parameters of an exploded view: explosion distance, direction, order, and the selection of explosion components. We propose two strategies, namely the structure-derived exploded view and the interactive free-form exploded view, for computing these four parameters systematically. The first strategy allows scientists to automatically create exploded views by computing the parameters from the given object structures. The second strategy further supports them to design and customize detailed explosion paths through user interaction. Our approach features the possibility to animate exploded views, to incorporate ease functions into these animations and to display the explosion path of components via arrows. Finally, we demonstrate three use cases with various challenges that we investigated in collaboration with a domain scientist. Our approach, therefore, provides interesting new ways of investigating and presenting the design layout and composition of complex molecular structures.",
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In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
\r\n",
"abstract": "In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
"abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
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\r\n\r\nInvited Talks
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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"short_abstract": "In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
\r\n",
"abstract": "In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
"abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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"id": "moerth-2018-tpose",
"type_id": "masterthesis",
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"title": "Interactive Reformation of Fetal Ultrasound Data to a T-Position",
"date": "2019-03-05",
"abstract": "Three dimensional ultrasound images are commonly used in prenatal screening. The acquisition delivers detailed information about the skin as well as the inner organs of the fetus. Prenatal screenings in terms of growth analysis are very important to support a healthy development of the fetus. The analysis of this data involves viewing of two dimensional (2D) slices in order to take measurements or calculate the volume and weight of the fetus. These steps involve manual investigation and are dependent on the skills of the person who performs them. These measurements and calculations are very important to analyze the development of the fetus and for the birth preparation.\nUltrasound imaging is a˙ected by artifacts like speckles, noise and also of structures obstructing the regions of interest. These artifacts occur because the imaging technique is using sound waves and their echo to create images. 2D slices as used as basis for the measurement of the fetus therefore might not be the best solution. Analyzing the data in a three dimensional (3D) way would enable the viewer to have a better overview and to better distinguish between artifacts and the real data of the fetus. The growth of a fetus can be analysed by comparing standardized measurements like the crown foot length, the femur length or the derived head circumference as well as the abdominal circumference.\nStandardization is well known in many fields of medicine and is used to enable compa-rability between investigations of the same patient or between patients. Therefore we introduce a standardized way of analyzing 3D ultrasound images of fetuses. Bringing the fetus in a standardized position would enable automatized measurements by the machine and there could also be new measurements applied like the volume of specific body parts. A standardized pose would also provide possibilities to compare the re-sults of di˙erent measurements of one fetus as well as the measurements of di˙erent fetuses.\nThe novel method consists of six steps, namely the loading of the data, the preprocessing, the rigging of the model, the weighting of the data, the actual transformation called the \"Vitruvian Baby\" and at the end the analysis of the result. We tried to automatize the workflow as far as possible resulting in some manual tasks and some automatic ones. The loading of the data works with standard medical image formats and the preprocessing involves some interaction in order to get rid of the ultrasound induced artifacts. Transforming data into a specific position is a complex task which might involve a manual processing steps. In the method presented in this work one step of the transformation namely the rigging of the model, where a skeleton is placed in the data, is performed manually. The weighting as well as the transformation although are performed completely automatically resulting in a T-pose representation of the data.\nWe analysed the performance of our novel approach in several ways. We first use a phantom model which has been used as a reference already presented in a T-pose. After using seven di˙erent fetus poses of the model as input the result was an average of 79,02%voxel overlapping between the output of the method and the goal T-pose. When having a look at the similarity of the finger to finger span and the head to toe measurement we considered a value of 91,08% and 94,05% in average. The time needed for the most complex manual task was in average seven minutes. After using a phantom model of a man, we also assessed the performance of the method using a computer model of a fetus and a phantom model of a 3D ultrasound investigation. The results also look very promising.",
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\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
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\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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{
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"title": "Semantic Screen-Space Occlusion for Multiscale Molecular Visualization",
"date": "2018-01-01",
"abstract": "When visualizing large biological data sets the problem of visual clutter arises. This\nproblem is often counteracted with level of detail schemes and appropriate coloring of the visualized structures. Ambient occlusion and shadows are often used in order to improve the depth perception which however promote visual clutter when used excessively. In this work an approach is explored to utilize screen-space shading techniques to reduce the visual clutter by using hierarchy information that is provided with molecular models.\nThis is achieved by selectively applying screen-space shading techniques based on the semantics of the visualized hierarchically structured data. This technique is demonstrated by implementing a hierarchy-aware version of screen-space directional occlusion and screen-space ray traced shadows into Marion, an interactive rendering system to visualize biological data.",
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
"abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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"type_id": "bachelorthesis",
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"title": "Visualization of Fiber Orientation in Glass Fiber Reinforced Polymers",
"date": "2018-01",
"abstract": "Fiber-reinforced composites are materials used for their extraordinary characteristics. The importance of these materials is constantly increasing, therefore, a wide range of variations exists of this material. Types range from Carbon Fiber Reinforced Polymer to Fiber-reinforced Foamed Urethane and more. Fiber-reinforced composites are lightweight,\nstrong, and durable, among others and are therefore used for printed circuit boards,\nrailway sleepers, airplanes or Formula 1 vehicles. To assure that these materials provide the required quality, they need to be tested and analyzed. To analyze these materials or to be more exact, the fibers within, special tools are needed. The first step is to scan the material with a X-ray Computed Tomography (CT) and save it as a volumetric CT-image on a computer. Now this data can be used to analyze the structure and find flaws in the dataset. In this thesis, a program for a later integration in a software called open_iA to extend its range of features, is developed. Purpose of the developed program is to analyze the orientation of fibers in a dataset. The result will be visualized with two different graphs. One shows the orientation of the fibers, while the other shows how\nmany fibers are visible to the analyst. With the option of different configurations, it is possible to further specify these visualizations and get a better understanding of the underlying data.",
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\nhttps://github.com/illvisation/
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"abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n",
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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"short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ",
"abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n",
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
"abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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"end_date": "2020-12-31",
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{
"id": "WWTF",
"contract_number": "VRG11-010",
"comment": null
}
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"abstract": "Scientific illustrators communicate the cutting edge of research through their illustrations. There are numerous software tools that assist them with this job. Often they use professional modeling and animation 3D programs which are primarily used in games and movies industry. Because of that however these tools are not suitable for scientific illustration out of the box. There have been attempts to address this issue which brought tremendous results. This work focuses on visualization of structures and processes in biology, focusing mostly on the scales of nano- to micrometers. At this scale we often do not gain much by using hyper-realistic rendering style that the professional software aims for. Instead we want to employ more simplified style which helps to communicate the important story without losing much detail or scientific precision. The aim of this thesis is to push abilities of illustrators working on large scale molecular scenes. This is done by connecting two software packages—Maya and cellVIEW—combining the real-time rendering possibilities of cellVIEW and modeling and animation tools of Maya which results in more effective and efficient workflow.",
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"viola-2007-ort",
"viola-evr",
"Viola-Pondering-2017",
"viola-popular-article-2006",
"Viola-vistutillustrativevis",
"vis-foa",
"vitruvian_2019",
"Waldin_Nicholas_2016_Chameleon",
"Waldin_Nicholas_2016_Colormaps",
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"Waldin_Nicholas_2017_FlickerObserver",
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=935",
"__class": "Author"
}
],
"location": "Phoenix, Arizona",
"number": "1",
"volume": "24",
"research_areas": [
{
"id": "BioVis",
"drupal_id": 4127,
"name": "Biological Data Visualization",
"short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.",
"abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n",
"website": "https://www.cg.tuwien.ac.at/research/area/BioVis",
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"2017-kouril-illcell",
"Alharbi_2021",
"amirkhanov-2019-manylands",
"byska-2019-mdfc",
"cellVIEW_2015",
"cmolik-2020-tvcg",
"Dietrich_1",
"dietrich-2016-viseq2",
"Ehlers_PhD",
"eschner-2023-ims",
"eschner-blur-2022",
"Escribano_2017",
"Furmanova_2018",
"Gehrer-2017",
"Gehrer-2017-molmach",
"glinzner-2016-tex",
"Halladjian_2020",
"kapferer-2017-godot",
"klein_2017_IM",
"klein_2019_PGG",
"klein_2019_PHD",
"klein_2019_PMP",
"koch-2018-sso",
"Kolesar-Fractional-2016",
"kolesar-ivan-2014-polymers",
"kouril-2015-maya2cellview",
"kouril-2017-sccgposter",
"kouril-2021-molecumentary",
"kouril-2021-phdthesis",
"Kozlikova-Visualization-2016b",
"Krone2016VABC",
"Kugler_2019",
"lemuzic_2015_timelapse",
"lemuzic-2014-ivm",
"lemuzic-2015-hiv",
"lemuzic-mindek-2016-viseq",
"lipp-2017-mgpu",
"lipp-2017-vulkan",
"Manczarski-2016",
"manylands_award",
"Miao_2019",
"miao_inria_2017",
"miao_nantech_2019",
"miao_nar_2020",
"miao_stateKeylabTalk_2017",
"miao_thesis_2019",
"miao_tvcg_2018",
"miao2018Dimsum",
"Miao2018FDN",
"mindek-2016-utah-talk",
"mindek-2017-marion",
"mindek-2017-virtualcell",
"mindek-2018-fyi",
"mindek-xmas-card-2016",
"Mitterhofer_2017",
"nguyen_2020-covid",
"Nowak_2020",
"raidou_2019_springer",
"raidou_shonan167",
"raidou2018visualflatter",
"rasch-2016-imgses",
"Reisacher2016",
"rinortner_susanne-2019-vpicc",
"Sarkis_2021",
"sbardellati_ba_2018",
"Sbardellati-2019-vcbm",
"sMolBoxes_2022",
"Sorger_2013_nMI",
"sorger_2017_metamorphers",
"sorger-2013-neuromap",
"sorger-2016-fowardabstraction",
"sorger-2017-thesis",
"stappen_2017_animatedcomic",
"Strohmayer-2018-BT",
"sturl_2016_dynlabels",
"trautner-2018-imd",
"unger-2019_vcp",
"vad_2015_phd",
"vad_viktor-2017-WVE",
"vad-2016-bre",
"Viola_Ivan_2013_SVA",
"Viola_Ivan_2013_VCA",
"Viola_Ivan_2015_AAM",
"Viola_Ivan_2015_MCT",
"Viola_Ivan_2015_VBS",
"Viola_Ivan_CLD",
"Viola_Ivan_IIP",
"waldin-2019-ccm",
"waldner-2014-af",
"Weissenboeck_2019",
"wu-2017-dagstuhl",
"wu-2018-metabo",
"wu-2018-story",
"wu-2019-bmc",
"wu-2019-report",
"wu-2019-vcbm",
"wu-2019-visworkshop",
"wu-2020-tvcg"
],
"projects": [
"BioNetIllustration",
"Illustrare",
"illvisation"
],
"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis",
"__class": "ResearchArea"
},
{
"id": "IllVis",
"drupal_id": 4131,
"name": "Illustrative Visualization",
"short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.",
"abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.",
"website": "https://www.cg.tuwien.ac.at/research/area/IllVis",
"teaser": {
"name": "teaser.jpg",
"path": "research_area:IllVis",
"type": "image/jpeg",
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"thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png",
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"2017-kouril-illcell",
"Alharbi_2021",
"Antonini2020",
"Balabanian-2010-IIV",
"Balduz_01",
"Bayat_2019",
"Bechtold2020",
"Birkeland-2012-IMC",
"brandstaetter_01",
"bruckner-2005-ICV",
"bruckner-2006-ICE",
"bruckner-2007-STF",
"bruckner-2008-IIV",
"bruckner-2010-HVC",
"bruckner-2010-IFC",
"cellVIEW_2015",
"Chen-Information-2016",
"Deutsch-2018",
"Dhanoa_2021",
"dietrich-2016-viseq2",
"donabauer_2019_1",
"eg-tut2005-iv",
"eschner-2023-ims",
"Essler2022",
"gangl-2018-gpsart",
"Gehrer_Daniel_CUI",
"Gehrer-2017-molmach",
"gerl-2006-vhi",
"Gogel2020",
"Groeller_2011_IPV",
"Groeller_2016_I3",
"Groeller_2016_I6",
"Groeller_2016_I7",
"Groeller_2016_I8",
"Groeller_V1_2020",
"groeller-2006-ivt",
"groeller-2007-fci",
"groeller-2008-irs",
"Groeller-2010-IFI",
"Halladjian_2020",
"haushofer-2018-skinning",
"Heim_2020",
"horvath-2018-ism",
"klein_2019_PGG",
"klein_2019_PHD",
"klein_2019_PMP",
"Knapp_2017_CVR",
"Koeppel2020",
"kolesar-ivan-2014-polymers",
"Konev-FCV2018",
"Koszticsak-2017-ewt",
"Kouril_2017_11",
"kouril-2020-hyperlabels",
"kouril-2021-molecumentary",
"kouril-2021-phdthesis",
"kroesl_x_card_2017",
"Lackner_2022",
"Langer_Edith_IR1",
"lawonn-2018-illvisstar",
"lemuzic_2014_ipv",
"lemuzic_2015_timelapse",
"LeMuzic_2016_PhD",
"lemuzic-2014-ivm",
"lemuzic-2015-hiv",
"lemuzic-mindek-2016-viseq",
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"Mautner 2020",
"Mayr-2017-1",
"Melo_2018_11",
"Meusburger_2020",
"Miao_2019",
"miao_inria_2017",
"miao_kaust_2018",
"miao_nantech_2019",
"miao_nar_2020",
"miao_stateKeylabTalk_2017",
"miao2018Dimsum",
"Michl_2017_CSV",
"mindek-2015-mc",
"mindek-2016-utah-talk",
"mindek-2017-marion",
"mindek-2017-virtualcell",
"mindek-2018-fyi",
"mindek-2019-mci",
"mindek-xmas-card-2016",
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"Ortner_PhD",
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"patel_daniel_2007_IRSD",
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"seyfert-2017",
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"sorger_2017_metamorphers",
"sorger-2016-fowardabstraction",
"sorger-2017-thesis",
"Spechtenhauser_Florian_2016",
"stappen_2017_animatedcomic",
"Stoll2020",
"sturl_2016_dynlabels",
"Swoboda2020",
"szabo_patrik-2022-tour",
"takahashi-2019-acdt",
"Thomas-2018",
"TR-186-2-07-08",
"Troidl_2021",
"Troidl_2022",
"tut-eg-2006",
"tut-siggraph-2006",
"tut-vis-2006",
"tut-vis-2007",
"Unger2020",
"Vasileva_2022",
"Viola_Ivan_2013_SVA",
"Viola_Ivan_CLD",
"Viola_Ivan_IIP",
"viola-evr",
"Viola-Pondering-2017",
"Viola-vistutillustrativevis",
"Waldin_Nicholas_2016_Colormaps",
"waldin-2019-ccm",
"Waldner_2017_11",
"Wihann_2017",
"Woschizka_2021",
"wu-2019-bmc",
"wu-2019-report",
"Zaufel_2021",
"zechmeister2020",
"Zeng_2021",
"Zusag-2017-Bach"
],
"projects": [
"Illustrare",
"illvisation"
],
"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis",
"__class": "ResearchArea"
},
{
"id": "Rendering",
"drupal_id": 4134,
"name": "Rendering",
"short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.",
"abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.",
"website": "https://www.cg.tuwien.ac.at/research/area/Rendering",
"teaser": {
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"path": "research_area:Rendering",
"type": "image/png",
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"2018_Mautner_Praktikum",
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"Artusi-2003-Del",
"ASCHL-2022-OTV",
"Auzinger_2012_AAA",
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"Auzinger_2014_UJA",
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"bernhard-2014-GTOM",
"bhagvat-09-frusta",
"birsak-2013-sta",
"Bittner-2001-Vis",
"Bittner-2003-Vis",
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"bittner-2011-scc",
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"cardoso-2021-cost",
"cardoso-2022-rtpercept",
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"TR-186-2-07-09",
"TR-186-2-08-09",
"TR-186-2-12-01",
"traxler-1997-TRA",
"Tucek_2018",
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"ulschmid-phdthesis",
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"unterguggenberger-2021-msh",
"unterguggenberger-2022-vulkan",
"VASCO-2019-EVR",
"wagner-2024-par",
"wallner-2015-ModelingRoutinization",
"Wang-2016-BAC",
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"abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n",
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"abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
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\r\n\r\ncellVIEW
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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"abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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"title": "MoleCollar and Tunnel Heat Map Visualizations for Conveying Spatio-Temporo-Chemical Properties Across and Along Protein Voids",
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"abstract": "Studying the characteristics of proteins and their inner void space, including their geometry, physico-chemical properties and dynamics are instrumental for evaluating the reactivity of the protein with other small molecules. The analysis of long simulations of molecular dynamics produces a large number of voids which have to be further explored and evaluated. In this paper we propose three new methods: two of them convey important properties along the long axis of a selected void during molecular dynamics and one provides a comprehensive picture across the void. The first two proposed methods use a specific heat map to present two types of information: an overview of all detected tunnels in the dynamics and their bottleneck width and stability over time, and an overview of a specific tunnel in the dynamics showing the bottleneck position and changes of the tunnel length over time. These methods help to select a small subset of tunnels, which are explored individually and in detail. For this stage we propose the third method, which shows in one static image the temporal evolvement of the shape of the most critical tunnel part, i.e., its bottleneck. This view is enriched with abstract depictions of different physicochemical properties of the amino acids surrounding the bottleneck. The usefulness of our newly proposed methods is demonstrated on a case study and the feedback from the domain experts is included. The biochemists confirmed that our novel methods help to convey the information about the appearance and properties of tunnels in a very intuitive and comprehensible manner.",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
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\r\n\r\nInvited Talks
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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"short_abstract": "The projects develops new mathematical foundations for global-illumination algorithms.",
"abstract": "Creating photorealistic images has always been an essential goal in computer graphics. The image generation process builds on a complex mathematical construct, the so-called rendering equation. This equation defines how light interacts with surfaces in a virtual scene, and involves complex surface description models that describe important effects like reflections, glossy surface interactions, and indirect illumination. Solving this equation can be achieved by investing a large amount of time and computational resources, but intelligent methods have been found that greatly speed up the calculations up to an interactive or even real-time frame rates. Both interactive as well as any non-interactive applications such as computer games, visual effects, architectural lighting simulation, urban and automotive design, disaster simulation and many other applications that depend on an accurate light simulation, profit from efficient ways to calculate light transport.\nThese methods can be categorized by being a part of the mathematical field of functional analysis where a large body of research exists because it forms the basis for scientific fields such as quantum mechanics, chaos and ergodic theory, vision and signal processing besides countless specialized applications in areas like structural mechanics, simulation and other engineering problems. Applications of Fourier or Laplace transformations, Spherical Harmonics or Wavelets, just to name a few important approaches, are ubiquitous.\nHowever, despite the considerable amount of research work devoted to finding methods to calculate and analyze the complex light transport in a virtual scene, they remain challenging issues and many inherent properties of light transport are largely unknown.\nOver the course of the last 10 years, a more general form of wavelets, named anisotropic wavelets that introduce directionality to the basis definitions have been proposed. In particular, curvelets and contourlets have already proven to be powerful tools in astrophysics, seismology, fluid dynamics and vision due to their unique properties optimized for natural signals.\nYet, anisotropic wavelets have not been considered for light transport, though they have several advantages over standard wavelets such as a higher sparsity or near-optimal representation. Therefore, the main goal of this project is to develop methods based on anisotropic wavelets that calculate all aspects of light transport more efficiently, delivering a higher image quality with fewer resources, including an adaptation to all principal domains used in computer graphics. Due to their properties, anisotropic wavelets also form an excellent foundation to perform a fundamental multi-scale and multi-directional analysis of light transport which leads to a better understanding and deeper into the process of light transport in virtual scenes.\n",
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
"abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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\r\n\r\ncellVIEW
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\r\n\r\nInvited Talks
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
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\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
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"short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
\r\n\r\ncellVIEW
\r\n\r\ncellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\nInvited Talks
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
\r\n",
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"end_date": "2020-12-31",
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{
"id": "WWTF",
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