EuroVA2023
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Browsing EuroVA2023 by Author "Miksch, Silvia"
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Item A Methodology for Task-Driven Guidance Design(The Eurographics Association, 2023) Pérez-Messina, Ignacio; Ceneda, Davide; Miksch, Silvia; Angelini, Marco; El-Assady, MennatallahMixed-initiative Visual Analytics (VA) systems are becoming increasingly important; however, the design of such systems still needs to be formulated. We present a methodology to aid and structure the design of guidance for mixed-initiative VA systems consisting of four steps: (1) defining the target of analysis, (2) identifying the user search tasks, (3) describing the system guidance tasks, and (4) specifying which and when guidance is provided. In summary, it specifies a space of possible user tasks and then maps it to the corresponding space of guidance tasks, using recent VA task typologies for guidance and visualizations. We illustrate these steps through a case study in a real-world model-building task involving decision-making with unevenlyspaced time-oriented data. Our methodology's goal is to enrich existing VA systems with guidance, being its output a structured description of a complex guidance task schema.Item Multi-Ensemble Visual Analytics via Fuzzy Sets(The Eurographics Association, 2023) Piccolotto, Nikolaus; Bögl, Markus; Miksch, Silvia; Angelini, Marco; El-Assady, MennatallahAnalysis of ensemble datasets, i.e., collections of complex elements such as geochemical maps, is widespread in science and industry. The elements' complexity arises from the data they capture, which are often multivariate or spatio-temporal. We speak of multi-ensemble datasets when the analysis pertains to multiple ensembles. While many visualization approaches were suggested for ensemble datasets, multi-ensemble datasets remain comparatively underexplored. Our years-long collaboration with statisticians and geochemists taught us that they frame many questions about multi-ensemble data as set operations. E.g., what are the most common members (intersection of ensembles), or what features exist in one member but not another (difference of members)? As classical crisp set relations cannot account for the elements' complexity, we propose to model multi-ensembles as fuzzy relations. We provide examples of fuzzy set-based queries on a multi-ensemble of geochemical maps and integrate this approach into an existing ensemble visualization pipeline. We evaluated two visualizations obtained by applying this pipeline with experts in geochemistry and statistics. The experts confirmed known information and got directions for further research, which is one Visual Analytics (VA) goal. Hence, our proposal is highly promising for an interactive VA approach.