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  1. Article: Visual Parameter Space Exploration in Time and Space.

    Piccolotto, Nikolaus / Bögl, Markus / Miksch, Silvia

    Computer graphics forum : journal of the European Association for Computer Graphics

    2023  Volume 42, Issue 6, Page(s) e14785

    Abstract: Computational models, such as simulations, are central to a wide range of fields in science and industry. Those models take input parameters and produce some output. To fully exploit their utility, relations between parameters and outputs must be ... ...

    Abstract Computational models, such as simulations, are central to a wide range of fields in science and industry. Those models take input parameters and produce some output. To fully exploit their utility, relations between parameters and outputs must be understood. These include, for example, which parameter setting produces the best result (optimization) or which ranges of parameter settings produce a wide variety of results (sensitivity). Such tasks are often difficult to achieve for various reasons, for example, the size of the parameter space, and supported with visual analytics. In this paper, we survey visual parameter space exploration (VPSE) systems involving spatial and temporal data. We focus on interactive visualizations and user interfaces. Through thematic analysis of the surveyed papers, we identify common workflow steps and approaches to support them. We also identify topics for future work that will help enable VPSE on a greater variety of computational models.
    Language English
    Publishing date 2023-04-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 1482655-0
    ISSN 1467-8659 ; 0167-7055
    ISSN (online) 1467-8659
    ISSN 0167-7055
    DOI 10.1111/cgf.14785
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Data Type Agnostic Visual Sensitivity Analysis.

    Piccolotto, Nikolaus / Bogl, Markus / Muehlmann, Christoph / Nordhausen, Klaus / Filzmoser, Peter / Schmidt, Johanna / Miksch, Silvia

    IEEE transactions on visualization and computer graphics

    2023  Volume PP

    Abstract: Modern science and industry rely on computational models for simulation, prediction, and data analysis. Spatial blind source separation (SBSS) is a model used to analyze spatial data. Designed explicitly for spatial data analysis, it is superior to ... ...

    Abstract Modern science and industry rely on computational models for simulation, prediction, and data analysis. Spatial blind source separation (SBSS) is a model used to analyze spatial data. Designed explicitly for spatial data analysis, it is superior to popular non-spatial methods, like PCA. However, a challenge to its practical use is setting two complex tuning parameters, which requires parameter space analysis. In this paper, we focus on sensitivity analysis (SA). SBSS parameters and outputs are spatial data, which makes SA difficult as few SA approaches in the literature assume such complex data on both sides of the model. Based on the requirements in our design study with statistics experts, we developed a visual analytics prototype for data type agnostic visual sensitivity analysis that fits SBSS and other contexts. The main advantage of our approach is that it requires only dissimilarity measures for parameter settings and outputs (Fig. 1). We evaluated the prototype heuristically with visualization experts and through interviews with two SBSS experts. In addition, we show the transferability of our approach by applying it to microclimate simulations. Study participants could confirm suspected and known parameter-output relations, find surprising associations, and identify parameter subspaces to examine in the future. During our design study and evaluation, we identified challenging future research opportunities.
    Language English
    Publishing date 2023-11-03
    Publishing country United States
    Document type Journal Article
    ISSN 1941-0506
    ISSN (online) 1941-0506
    DOI 10.1109/TVCG.2023.3327203
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: Data Type Agnostic Visual Sensitivity Analysis

    Piccolotto, Nikolaus / Bögl, Markus / Muehlmann, Christoph / Nordhausen, Klaus / Filzmoser, Peter / Schmidt, Johanna / Miksch, Silvia

    2023  

    Abstract: Modern science and industry rely on computational models for simulation, prediction, and data analysis. Spatial blind source separation (SBSS) is a model used to analyze spatial data. Designed explicitly for spatial data analysis, it is superior to ... ...

    Abstract Modern science and industry rely on computational models for simulation, prediction, and data analysis. Spatial blind source separation (SBSS) is a model used to analyze spatial data. Designed explicitly for spatial data analysis, it is superior to popular non-spatial methods, like PCA. However, a challenge to its practical use is setting two complex tuning parameters, which requires parameter space analysis. In this paper, we focus on sensitivity analysis (SA). SBSS parameters and outputs are spatial data, which makes SA difficult as few SA approaches in the literature assume such complex data on both sides of the model. Based on the requirements in our design study with statistics experts, we developed a visual analytics prototype for data type agnostic visual sensitivity analysis that fits SBSS and other contexts. The main advantage of our approach is that it requires only dissimilarity measures for parameter settings and outputs. We evaluated the prototype heuristically with visualization experts and through interviews with two SBSS experts. In addition, we show the transferability of our approach by applying it to microclimate simulations. Study participants could confirm suspected and known parameter-output relations, find surprising associations, and identify parameter subspaces to examine in the future. During our design study and evaluation, we identified challenging future research opportunities.
    Keywords Computer Science - Human-Computer Interaction
    Subject code 310
    Publishing date 2023-09-07
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Book ; Online: Visual Parameter Selection for Spatial Blind Source Separation

    Piccolotto, Nikolaus / Bögl, Markus / Muehlmann, Christoph / Nordhausen, Klaus / Filzmoser, Peter / Miksch, Silvia

    2021  

    Abstract: Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are integral to many domains, e.g., indicators of valuable minerals are measured for mine ... ...

    Abstract Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are integral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non-expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data.
    Keywords Computer Science - Human-Computer Interaction
    Subject code 004
    Publishing date 2021-12-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article: Guide Me in Analysis: A Framework for Guidance Designers.

    Ceneda, Davide / Andrienko, Natalia / Andrienko, Gennady / Gschwandtner, Theresia / Miksch, Silvia / Piccolotto, Nikolaus / Schreck, Tobias / Streit, Marc / Suschnigg, Josef / Tominski, Christian

    Computer graphics forum : journal of the European Association for Computer Graphics

    2020  Volume 39, Issue 6, Page(s) 269–288

    Abstract: Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed ...

    Abstract Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approach this problem from the perspective of guidance designers. We present a framework comprising requirements and a set of specific phases designers should go through when designing guidance for visual analytics. We relate this process with a set of quality criteria we aim to support with our framework, that are necessary for obtaining a suitable and effective guidance solution. To demonstrate the practical usability of our methodology, we apply our framework to the design of guidance in three analysis scenarios and a design walk-through session. Moreover, we list the emerging challenges and report how the framework can be used to design guidance solutions that mitigate these issues.
    Language English
    Publishing date 2020-05-16
    Publishing country England
    Document type Journal Article
    ZDB-ID 1482655-0
    ISSN 1467-8659 ; 0167-7055
    ISSN (online) 1467-8659
    ISSN 0167-7055
    DOI 10.1111/cgf.14017
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

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  6. Book ; Online: TBSSvis

    Piccolotto, Nikolaus / Bögl, Markus / Gschwandtner, Theresia / Muehlmann, Christoph / Nordhausen, Klaus / Filzmoser, Peter / Miksch, Silvia

    Visual Analytics for Temporal Blind Source Separation

    2020  

    Abstract: Temporal Blind Source Separation (TBSS) is used to obtain the true underlying processes from noisy temporal multivariate data, such as electrocardiograms. TBSS has similarities to Principal Component Analysis (PCA) as it separates the input data into ... ...

    Abstract Temporal Blind Source Separation (TBSS) is used to obtain the true underlying processes from noisy temporal multivariate data, such as electrocardiograms. TBSS has similarities to Principal Component Analysis (PCA) as it separates the input data into univariate components and is applicable to suitable datasets from various domains, such as medicine, finance, or civil engineering. Despite TBSS's broad applicability, the involved tasks are not well supported in current tools, which offer only text-based interactions and single static images. Analysts are limited in analyzing and comparing obtained results, which consist of diverse data such as matrices and sets of time series. Additionally, parameter settings have a big impact on separation performance, but as a consequence of improper tooling, analysts currently do not consider the whole parameter space. We propose to solve these problems by applying visual analytics (VA) principles. Our primary contribution is a design study for TBSS, which so far has not been explored by the visualization community. We developed a task abstraction and visualization design in a user-centered design process. Task-specific assembling of well-established visualization techniques and algorithms to gain insights in the TBSS processes is our secondary contribution. We present TBSSvis, an interactive web-based VA prototype, which we evaluated extensively in two interviews with five TBSS experts. Feedback and observations from these interviews show that TBSSvis supports the actual workflow and combination of interactive visualizations that facilitate the tasks involved in analyzing TBSS results.
    Keywords Computer Science - Human-Computer Interaction
    Subject code 006 ; 004
    Publishing date 2020-11-19
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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