@inproceedings{rind_trustworthy_2022, title = {Trustworthy {Visual} {Analytics} in {Clinical} {Gait} {Analysis}: {A} {Case} {Study} for {Patients} with {Cerebral} {Palsy}}, isbn = {978-1-66549-356-7}, url = {https://arxiv.org/abs/2208.05232}, doi = {10.1109/TREX57753.2022.00006}, abstract = {Three-dimensional clinical gait analysis is essential for selecting optimal treatment interventions for patients with cerebral palsy (CP), but generates a large amount of time series data. For the automated analysis of these data, machine learning approaches yield promising results. However, due to their black-box nature, such approaches are often mistrusted by clinicians. We propose gaitXplorer, a visual analytics approach for the classification of CP-related gait patterns that integrates Grad-CAM, a well-established explainable artificial intelligence algorithm, for explanations of machine learning classifications. Regions of high relevance for classification are highlighted in the interactive visual interface. The approach is evaluated in a case study with two clinical gait experts. They inspected the explanations for a sample of eight patients using the visual interface and expressed which relevance scores they found trustworthy and which they found suspicious. Overall, the clinicians gave positive feedback on the approach as it allowed them a better understanding of which regions in the data were relevant for the classification.}, booktitle = {Proc. 2022 {IEEE} {Workshop} on {TRust} and {EXpertise} in {Visual} {Analytics} ({TREX})}, publisher = {IEEE}, author = {Rind, Alexander and Slijepcevic, Djordje and Zeppelzauer, Matthias and Unglaube, Fabian and Kranzl, Andreas and Horsak, Brian}, year = {2022}, note = {Projekt: SoniVis Projekt: ReMoCap-Lab Projekt: I3D}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Data Science, Departement Medien und Digitale Technologien, Department Gesundheit, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Human-Computer Interaction, Institut für Creative Media Technologies, Machine Learning, SP CDHSI Motor Rehabilitation, Schriftpublikation, Visual Computing, Visualization, Vortrag, Wiss. Beitrag, best, best-arind, peer-reviewed}, pages = {7--15}, } @inproceedings{rind_pubviz_2017, title = {{PubViz}: {Lightweight} {Visual} {Presentation} of {Publication} {Data}}, url = {https://phaidra.fhstp.ac.at/download/o:4834}, doi = {10/cwdc}, abstract = {Publications play a central role in presenting the outcome of scientific research but are typically presented as textual lists, whereas related work in visualization of publication focuses on exploration – not presentation. To bridge this gap, we conducted a design study of an interactive visual representation of publication data in a BibTeX file. This paper reports our domain and problem characterization as well as our visualization design decisions in light of our user-centered design process including interviews, two user studies with a paper prototype and a d3.js prototype, and practical application at our group’s website.}, booktitle = {Proc. {Eurographics} {Conf}. {Visualization} ({EuroVis}) – {Short} {Paper}}, publisher = {EuroGraphics}, author = {Rind, Alexander and Haberson, Andrea and Blumenstein, Kerstin and Niederer, Christina and Wagner, Markus and Aigner, Wolfgang}, editor = {Kozlíková, Barbora and Schreck, Tobias and Wischgoll, Thomas}, month = jun, year = {2017}, note = {Projekt: VisOnFire Projekt: KAVA-Time Projekt: VALID}, keywords = {Design Study, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, User-Centered Design, Vortrag, Wiss. Beitrag, best, best-arind, bibliography, interactive, peer-reviewed, prototype, publication list, visual presentation, visualization}, pages = {169--173}, } @article{rind_interactive_2013, title = {Interactive {Information} {Visualization} to {Explore} and {Query} {Electronic} {Health} {Records}}, volume = {5}, url = {https://publik.tuwien.ac.at/files/PubDat_214284.pdf}, doi = {10/f3szvd}, number = {3}, urldate = {2019-10-04}, journal = {Foundations and Trends in Human–Computer Interaction}, author = {Rind, Alexander and Wang, Taowei David and Aigner, Wolfgang and Miksch, Silvia and Wongsuphasawat, Krist and Plaisant, Catherine and Shneiderman, Ben}, year = {2013}, note = {00000}, keywords = {Extern, best-arind, best-lbaigner}, pages = {207--298}, } @article{andrienko_viewing_2018, title = {Viewing {Visual} {Analytics} as {Model} {Building}}, volume = {37}, url = {http://openaccess.city.ac.uk/19078/}, doi = {10/gdv9s7}, abstract = {To complement the currently existing definitions and conceptual frameworks of visual analytics, which focus mainly on activities performed by analysts and types of techniques they use, we attempt to define the expected results of these activities. We argue that the main goal of doing visual analytics is to build a mental and/or formal model of a certain piece of reality reflected in data. The purpose of the model may be to understand, to forecast or to control this piece of reality. Based on this model-building perspective, we propose a detailed conceptual framework in which the visual analytics process is considered as a goal-oriented workflow producing a model as a result. We demonstrate how this framework can be used for performing an analytical survey of the visual analytics research field and identifying the directions and areas where further research is needed.}, number = {6}, journal = {Computer Graphics Forum}, author = {Andrienko, Natalia and Lammarsch, Tim and Andrienko, Gennady and Fuchs, Georg and Keim, Daniel A. and Miksch, Silvia and Rind, Alexander}, year = {2018}, note = {Projekt: KAVA-Time}, keywords = {FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Visual analytics, Wiss. Beitrag, analytical process, best, best-arind, knowledge generation, peer-reviewed, theory and model}, pages = {275--299}, } @article{rind_task_2016, title = {Task {Cube}: {A} {Three}-{Dimensional} {Conceptual} {Space} of {User} {Tasks} in {Visualization} {Design} and {Evaluation}}, volume = {15}, url = {https://publik.tuwien.ac.at/files/PubDat_247156.pdf}, doi = {10/f3szvq}, abstract = {User tasks play a pivotal role in visualization design and evaluation. However, the term ‘task’ is used ambiguously within the visualization community. In this article, we critically analyze the relevant literature and systematically compare definitions for ‘task’ and the usage of related terminology. In doing so, we identify a three-dimensional conceptual space of user tasks in visualization, referred to as task cube, and the more precise concepts ‘objective’ and ‘action’ for tasks. We illustrate the usage of the task cube’s dimensions in an objective-driven visualization process, in different scenarios of visualization design and evaluation, and for comparing categorizations of abstract tasks. Thus, visualization researchers can better formulate their contributions which helps advance visualization as a whole.}, number = {4}, journal = {Information Visualization}, author = {Rind, Alexander and Aigner, Wolfgang and Wagner, Markus and Miksch, Silvia and Lammarsch, Tim}, year = {2016}, note = {Projekt: KAVA-Time Projekt: VALID}, keywords = {Action, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Visual Computing, Wiss. Beitrag, best, best-arind, best-lbaigner, best-lbwagnerm, design guidelines, interaction, objective, peer-reviewed, task frameworks, task taxonomy, terminology, visualization theory}, pages = {288--300}, } @article{rind_timebench_2013, title = {{TimeBench}: {A} {Data} {Model} and {Software} {Library} for {Visual} {Analytics} of {Time}-{Oriented} {Data}}, volume = {19}, url = {https://publik.tuwien.ac.at/files/PubDat_219700.pdf}, doi = {10/f3szvg}, abstract = {Time-oriented data play an essential role in many Visual Analytics scenarios such as extracting medical insights from collections of electronic health records or identifying emerging problems and vulnerabilities in network traffic. However, many software libraries for Visual Analytics treat time as a flat numerical data type and insufficiently tackle the complexity of the time domain such as calendar granularities and intervals. Therefore, developers of advanced Visual Analytics designs need to implement temporal foundations in their application code over and over again. We present TimeBench, a software library that provides foundational data structures and algorithms for time-oriented data in Visual Analytics. Its expressiveness and developer accessibility have been evaluated through application examples demonstrating a variety of challenges with time-oriented data and long-term developer studies conducted in the scope of research and student projects.}, number = {12}, journal = {IEEE Transactions on Visualization and Computer Graphics}, author = {Rind, Alexander and Lammarsch, Tim and Aigner, Wolfgang and Alsallakh, Bilal and Miksch, Silvia}, year = {2013}, note = {00008}, keywords = {Extern, best-arind, best-lbaigner}, pages = {2247--2256}, }