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        "title": "Exploratory Visual System for Predictive Machine Learning of Event-Organisation Data",
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        "abstract": "In recent years, the usage of machine learning (ML) models and especially deep neural\nnetworks in many different domains has increased rapidly. One of the major challenges\nwhen working with ML models is to correctly and efficiently interpret the results given\nby a model. Additionally, understanding how the model came to its conclusions can be\na very complicated task even for domain experts in the field of machine learning. For\nlaypeople, ML models are often just black-boxes. The lack of understanding of a model\nand its reasoning often leads to users not trusting the model’s predictions.\n\nIn this thesis, we work with an ML model trained on event-organisation data. The\ngoal is to create an exploratory visual event-organisation system that enables event\norganisers to efficiently work with the model. The main user goals in this scenario are\nto maximise profits and to be able to prepare for the predicted number of visitors. To\nachieve these goals users need to be able to perform tasks like: interpreting the prediction\nof the current input and performing what-if analyses to understand the effects of\nchanging parameters. The proposed system incorporates adapted versions of multiple\nstate-of-the-art model-agnostic interpretation methods like partial dependence plots and\ncase-based reasoning. Since model-agnostic methods are independent of the ML model,\nthey provide high flexibility.\n\nMany state-of-the-art approaches to explain ML models are too complex to be understood\nby laypeople. Our target group of event organisers cannot be expected to have a sufficient\namount of technical knowledge in the field of machine learning. In this thesis, we want\nto find answers to the questions: How can we visualise ML predictions to laypeople in a\ncomprehensible way? How can predictions be compared against each other? How can\nwe support users in gaining trust in the ML model? Our event-organisation system is\ncreated using a human-centred design approach performing multiple case studies with\npotential users during the whole development circle.",
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        "diploma_examina": "2021-11-15",
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        "id": "Sbardellati-2019-vcbm",
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        "tu_id": 282838,
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        "title": "Interactive Exploded Views for Molecular Structures",
        "date": "2019-09-03",
        "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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        "title": "Interactive Exploded Views for Presenting DNA Nano-Structures",
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        "abstract": "As the complexity of computer-aided-designed DNA nano-structures progresses day by day, the presentation of these structures is becoming complex. To tackle the main presentation problem, visual occlusion of structure components, we developed a semiautomated method to create effective interactive exploded views for DNA nano-structures, especially for educational purposes. This is done by displacing selected components of a DNA nano-structure based on the four key parameters explosion direction, distance,\norder and component selection. In this thesis we describe three different strategies of choosing the explosion direction, with two of them being defined by the object structure and one by the user. For the two structure defined approaches a method to calculate the explosion distance and three different explosion orders is described. The explosion components for these two approaches are defined by the hierarchical structure of the dataset, that describes the object. The user defined approach lets the user decide on the explosion distance and features one possible explosion order. It also lets the user select the explosion components arbitrarily. The developed application additionally features the possibility to animate an explosion and to use easing in these animations. ",
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