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  1. Artikel ; Online: Reclaiming the Horizon: Novel Visualization Designs for Time-Series Data with Large Value Ranges.

    Braun, Daniel / Borgo, Rita / Sondag, Max / von Landesberger, Tatiana

    IEEE transactions on visualization and computer graphics

    2023  Band 30, Heft 1, Seite(n) 1161–1171

    Abstract: We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which ... ...

    Abstract We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which extends the classic horizon graph; and (2) the order of magnitude line chart, which adapts the log-line chart. These new visualization designs visualize large value ranges by explicitly splitting the mantissa m and exponent e of a value v=m·10
    Sprache Englisch
    Erscheinungsdatum 2023-12-25
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1941-0506
    ISSN (online) 1941-0506
    DOI 10.1109/TVCG.2023.3326576
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Insights by Visual Comparison: The State and Challenges.

    von Landesberger, Tatiana

    IEEE computer graphics and applications

    2018  Band 38, Heft 3, Seite(n) 140–148

    Abstract: Data comparison is one of the core tasks in exploratory analysis, which combines algorithmic analysis and interactive visualization in a visual data comparison process. Comparison of large and complex datasets requires several steps-i.e., a workflow. ... ...

    Abstract Data comparison is one of the core tasks in exploratory analysis, which combines algorithmic analysis and interactive visualization in a visual data comparison process. Comparison of large and complex datasets requires several steps-i.e., a workflow. This article discusses the comparison process, its research challenges, and examples of solutions.
    Mesh-Begriff(e) Algorithms ; Computer Graphics ; Humans ; Research Design
    Sprache Englisch
    Erscheinungsdatum 2018-06-07
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1558-1756
    ISSN (online) 1558-1756
    DOI 10.1109/MCG.2018.032421661
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Buch ; Online: Reclaiming the Horizon

    Braun, Daniel / Borgo, Rita / Sondag, Max / von Landesberger, Tatiana

    Novel Visualization Designs for Time-Series Data with Large Value Ranges

    2023  

    Abstract: We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which ... ...

    Abstract We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which extends the classic horizon graph; and (2) the order of magnitude line chart, which adapts the log-line chart. These new visualization designs visualize large value ranges by explicitly splitting the mantissa m and exponent e of a value v = m * 10e . We evaluate our novel designs against the most relevant state-of-the-art visualizations in an empirical user study. It focuses on four main tasks commonly employed in the analysis of time-series and large value ranges visualization: identification, discrimination, estimation, and trend detection. For each task we analyse error, confidence, and response time. The new order of magnitude horizon graph performs better or equal to all other designs in identification, discrimination, and estimation tasks. Only for trend detection tasks, the more traditional horizon graphs reported better performance. Our results are domain-independent, only requiring time-series data with large value ranges.

    Comment: Preprint and Author Version of a Full Paper, accepted to the 2023 IEEE Visualization Conference (VIS)
    Schlagwörter Computer Science - Human-Computer Interaction ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Graphics
    Thema/Rubrik (Code) 306
    Erscheinungsdatum 2023-07-18
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: A Problem Space for Designing Visualizations.

    Gleicher, Michael / Riveiro, Maria / von Landesberger, Tatiana / Deussen, Oliver / Chang, Remco / Gillman, Christina / Rhyne, Theresa-Marie

    IEEE computer graphics and applications

    2023  Band 43, Heft 4, Seite(n) 111–120

    Abstract: Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, ...

    Abstract Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, and evaluate the things we create. The literature has many task structures (taxonomies, typologies, etc.), design spaces, and related "frameworks" that provide abstractions of the problems a visualization is meant to address. In this Visualization Viewpoints article, we introduce a different one, a problem space that complements existing frameworks by focusing on the needs that a visualization is meant to solve. We believe it provides a valuable conceptual tool for designing and discussing visualizations.
    Sprache Englisch
    Erscheinungsdatum 2023-07-11
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1558-1756
    ISSN (online) 1558-1756
    DOI 10.1109/MCG.2023.3267213
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Buch ; Online: A Problem Space for Designing Visualizations

    Gleicher, Michael / Riveiro, Maria / von Landesberger, Tatiana / Deussen, Oliver / Chang, Remco / Gillman, Christina

    2023  

    Abstract: Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, ...

    Abstract Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, and evaluate the things we create. The literature has many task structures (taxonomies, typologies, etc.), design spaces, and related ``frameworks'' that provide abstractions of the problems a visualization is meant to address. In this viewpoint, we introduce a different one, a problem space that complements existing frameworks by focusing on the needs that a visualization is meant to solve. We believe it provides a valuable conceptual tool for designing and discussing visualizations.

    Comment: Author's submitted version. An article with the same content was approved for publication by the Visualization Viewpoints Department of IEEE Computer Graphics and Applications magazine
    Schlagwörter Computer Science - Human-Computer Interaction
    Thema/Rubrik (Code) 306
    Erscheinungsdatum 2023-03-10
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: Visual Validation versus Visual Estimation

    Braun, Daniel / Suh, Ashley / Chang, Remco / Gleicher, Michael / von Landesberger, Tatiana

    A Study on the Average Value in Scatterplots

    2023  

    Abstract: We investigate the ability of individuals to visually validate statistical models in terms of their fit to the data. While visual model estimation has been studied extensively, visual model validation remains under-investigated. It is unknown how well ... ...

    Abstract We investigate the ability of individuals to visually validate statistical models in terms of their fit to the data. While visual model estimation has been studied extensively, visual model validation remains under-investigated. It is unknown how well people are able to visually validate models, and how their performance compares to visual and computational estimation. As a starting point, we conducted a study across two populations (crowdsourced and volunteers). Participants had to both visually estimate (i.e, draw) and visually validate (i.e., accept or reject) the frequently studied model of averages. Across both populations, the level of accuracy of the models that were considered valid was lower than the accuracy of the estimated models. We find that participants' validation and estimation were unbiased. Moreover, their natural critical point between accepting and rejecting a given mean value is close to the boundary of its 95% confidence interval, indicating that the visually perceived confidence interval corresponds to a common statistical standard. Our work contributes to the understanding of visual model validation and opens new research opportunities.

    Comment: Preprint and Author Version of a Short Paper, accepted to the 2023 IEEE Visualization Conference (VIS)
    Schlagwörter Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Graphics
    Thema/Rubrik (Code) 310
    Erscheinungsdatum 2023-07-18
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Automatisierte Surveillance und Risikovorhersage mit dem Ziel einer risikostratifizierten Infektionskontrolle und -prävention (RISK Prediction for Risk-stratified Infection Control and Prevention).

    Marschollek, Michael / Marquet, Mike / Reinoso Schiller, Nicolás / Naim, Joëlle / Aghdassi, Seven Johannes Sam / Behnke, Michael / Ehrenberg, Sandra / von Landesberger, Tatiana / Misailovski, Martin / Prasser, Fabian / Scherag, André / Schlueter, Dirk / Wulff, Antje / Pletz, Mathias / Scheithauer, Simone

    Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz

    2024  

    Abstract: Healthcare-associated infections (HCAIs) represent an enormous burden for patients, healthcare workers, relatives and society worldwide, including Germany. The central tasks of infection prevention are recording and evaluating infections with the aim of ... ...

    Titelübersetzung Automated surveillance and risk prediction with the aim of risk-stratified infection control and prevention (RISK PRINCIPE).
    Abstract Healthcare-associated infections (HCAIs) represent an enormous burden for patients, healthcare workers, relatives and society worldwide, including Germany. The central tasks of infection prevention are recording and evaluating infections with the aim of identifying prevention potential and risk factors, taking appropriate measures and finally evaluating them. From an infection prevention perspective, it would be of great value if (i) the recording of infection cases was automated and (ii) if it were possible to identify particularly vulnerable patients and patient groups in advance, who would benefit from specific and/or additional interventions.To achieve this risk-adapted, individualized infection prevention, the RISK PRINCIPE research project develops algorithms and computer-based applications based on standardised, large datasets and incorporates expertise in the field of infection prevention.The project has two objectives: a) to develop and validate a semi-automated surveillance system for hospital-acquired bloodstream infections, prototypically for HCAI, and b) to use comprehensive patient data from different sources to create an individual or group-specific infection risk profile.RISK PRINCIPE is based on bringing together the expertise of medical informatics and infection medicine with a focus on hygiene and draws on information and experience from two consortia (HiGHmed and SMITH) of the German Medical Informatics Initiative (MII), which have been working on use cases in infection medicine for more than five years.
    Sprache Deutsch
    Erscheinungsdatum 2024-05-16
    Erscheinungsland Germany
    Dokumenttyp English Abstract ; Journal Article ; Review
    ZDB-ID 1461973-8
    ISSN 1437-1588 ; 1436-9990
    ISSN (online) 1437-1588
    ISSN 1436-9990
    DOI 10.1007/s00103-024-03882-w
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Artikel ; Online: Typology of Uncertainty in Static Geolocated Graphs for Visualization.

    von Landesberger, Tatiana / Bremm, Sebastian / Wunderlich, Marcel

    IEEE computer graphics and applications

    2017  Band 37, Heft 5, Seite(n) 18–27

    Abstract: Static geolocated graphs have nodes connected by edges, where both can have geographic location and associated attributes. For example, it can be uncertain exactly where a node is located or whether an edge between two nodes exists. Because source data ... ...

    Abstract Static geolocated graphs have nodes connected by edges, where both can have geographic location and associated attributes. For example, it can be uncertain exactly where a node is located or whether an edge between two nodes exists. Because source data is often incomplete or inexact, it is necessary to visualize this uncertainty to help users make appropriate decisions. The proposed typology of uncertainty extends related typologies with specific features needed for characterizing uncertainty in static geolocated graphs.
    Sprache Englisch
    Erscheinungsdatum 2017-09-21
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1558-1756
    ISSN (online) 1558-1756
    DOI 10.1109/MCG.2017.3621220
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel ; Online: Visualization System Requirements for Data Processing Pipeline Design and Optimization.

    von Landesberger, Tatiana / Fellner, Dieter W / Ruddle, Roy A

    IEEE transactions on visualization and computer graphics

    2016  Band 23, Heft 8, Seite(n) 2028–2041

    Abstract: The rising quantity and complexity of data creates a need to design and optimize data processing pipelines-the set of data processing steps, parameters and algorithms that perform operations on the data. Visualization can support this process but, ... ...

    Abstract The rising quantity and complexity of data creates a need to design and optimize data processing pipelines-the set of data processing steps, parameters and algorithms that perform operations on the data. Visualization can support this process but, although there are many examples of systems for visual parameter analysis, there remains a need to systematically assess users' requirements and match those requirements to exemplar visualization methods. This article presents a new characterization of the requirements for pipeline design and optimization. This characterization is based on both a review of the literature and first-hand assessment of eight application case studies. We also match these requirements with exemplar functionality provided by existing visualization tools. Thus, we provide end-users and visualization developers with a way of identifying functionality that addresses data processing problems in an application. We also identify seven future challenges for visualization research that are not met by the capabilities of today's systems.
    Sprache Englisch
    Erscheinungsdatum 2016-08-25
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1941-0506
    ISSN (online) 1941-0506
    DOI 10.1109/TVCG.2016.2603178
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  10. Buch ; Online: Color Coding of Large Value Ranges Applied to Meteorological Data

    Braun, Daniel / Ebell, Kerstin / Schemann, Vera / Pelchmann, Laura / Crewell, Susanne / Borgo, Rita / von Landesberger, Tatiana

    2022  

    Abstract: This paper presents a novel color scheme designed to address the challenge of visualizing data series with large value ranges, where scale transformation provides limited support. We focus on meteorological data, where the presence of large value ranges ... ...

    Abstract This paper presents a novel color scheme designed to address the challenge of visualizing data series with large value ranges, where scale transformation provides limited support. We focus on meteorological data, where the presence of large value ranges is common. We apply our approach to meteorological scatterplots, as one of the most common plots used in this domain area. Our approach leverages the numerical representation of mantissa and exponent of the values to guide the design of novel "nested" color schemes, able to emphasize differences between magnitudes. Our user study evaluates the new designs, the state of the art color scales and representative color schemes used in the analysis of meteorological data: ColorCrafter, Viridis, and Rainbow. We assess accuracy, time and confidence in the context of discrimination (comparison) and interpretation (reading) tasks. Our proposed color scheme significantly outperforms the others in interpretation tasks, while showing comparable performances in discrimination tasks.

    Comment: Preprint and Author Version of a Short Paper, accepted to the 2022 IEEE Visualization Conference (VIS)
    Schlagwörter Electrical Engineering and Systems Science - Image and Video Processing ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Graphics
    Thema/Rubrik (Code) 004
    Erscheinungsdatum 2022-07-13
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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