@article{wagner_kavagait_2018, title = {{KAVAGait}: {Knowledge}-{Assisted} {Visual} {Analytics} for {Clinical} {Gait} {Analysis}}, volume = {25}, url = {https://doi.org/10.1109/TVCG.2017.2785271}, doi = {10/ghppzn}, abstract = {In 2014, more than 10 million people in the US were affected by an ambulatory disability. Thus, gait rehabilitation is a crucial part of health care systems. The quantification of human locomotion enables clinicians to describe and analyze a patient’s gait performance in detail and allows them to base clinical decisions on objective data. These assessments generate a vast amount of complex data which need to be interpreted in a short time period. We conducted a design study in cooperation with gait analysis experts to develop a novel Knowledge-Assisted Visual Analytics solution for clinical Gait analysis (KAVAGait). KAVAGait allows the clinician to store and inspect complex data derived during clinical gait analysis. The system incorporates innovative and interactive visual interface concepts, which were developed based on the needs of clinicians. Additionally, an explicit knowledge store (EKS) allows externalization and storage of implicit knowledge from clinicians. It makes this information available for others, supporting the process of data inspection and clinical decision making. We validated our system by conducting expert reviews, a user study, and a case study. Results suggest that KAVAGait is able to support a clinician during clinical practice by visualizing complex gait data and providing knowledge of other clinicians.}, number = {3}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, author = {Wagner, Markus and Slijepcevic, Djordje and Horsak, Brian and Rind, Alexander and Zeppelzauer, Matthias and Aigner, Wolfgang}, year = {2018}, note = {Projekt: KAVA-Time Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Design Study, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Healthcare, Human Gait Analysis, Human-Computer Interaction, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Visual analytics, Wiss. Beitrag, best, best-bhorsak, best-lbaigner, best-lbwagnerm, best-mzeppelzauer, information visualization, knowledge generation, peer-reviewed}, pages = {1528--1542}, } @inproceedings{blumenstein_evaluating_2016, address = {Baltimore, MD, USA}, title = {Evaluating {Information} {Visualization} on {Mobile} {Devices}: {Gaps} and {Challenges} in the {Empirical} {Evaluation} {Design} {Space}}, isbn = {978-1-4503-4818-8}, url = {https://phaidra.fhstp.ac.at/o:4873}, doi = {10/cwc6}, abstract = {With their increasingly widespread use, mobile devices have become a highly relevant target environment for Information Visualization. However, far too little attention has been paid to evaluation of interactive visualization techniques on mobile devices. To fill this gap, this paper provides a structured overview of the commonly used evaluation approaches for mobile visualization. For this, it systematically reviews the scientific literature of major InfoVis and HCI venues and categorizes the relevant work based on six dimensions circumscribing the design and evaluation space for visualization on mobile devices. Based on the 21 evaluations reviewed, reproducibility, device variety and usage environment surface as the three main issues in evaluation of information visualization on mobile devices. To overcome these issues, we argue for a transparent description of all research aspects and propose to focus more on context of usage and technology.}, booktitle = {Proceedings of 2016 {Workshop} on {Beyond} {Time} {And} {Errors}: {Novel} {Evaluation} {Methods} {For} {Visualization}}, publisher = {ACM}, author = {Blumenstein, Kerstin and Niederer, Christina and Wagner, Markus and Schmiedl, Grischa and Rind, Alexander and Aigner, Wolfgang}, year = {2016}, note = {Projekt: KAVA-Time Projekt: Couragierte Gemeinde Projekt: VALID Projekt: VisOnFire}, keywords = {Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, best, best-kblumenstein, best-lbaigner, best-lbwagnerm, evaluation, information visualization, mobile, peer-reviewed}, pages = {125--132}, } @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}, } @misc{aigner_visual_2021, address = {Kremsmünster, Austria}, type = {Invited {Talk}}, title = {Visual {Analytics} for {Time}-{Oriented} {Data}}, author = {Aigner, Wolfgang}, month = mar, year = {2021}, note = {Projekt: KAVA-Time Projekt: IML Projekt: InnoFit Projekt: SoniVis}, keywords = {FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Smart Manufacturing, Visualization, Vortrag}, } @inproceedings{rind_bridging_2018, title = {Bridging the {Gap} {Between} {Sonification} and {Visualization}}, url = {https://doi.org/10.5281/zenodo.6510341}, doi = {10.5281/zenodo.6510341}, abstract = {Extensive research has been carried out both on auditory and visual representation of data. Still, there is huge potential for complementary audio-visual analytics environments. This position paper works towards a research agenda for interdisciplinary work.}, booktitle = {Proc. {AVI} {Workshop} on {Multimodal} {Interaction} for {Data} {Visualization} ({MultimodalVis})}, author = {Rind, Alexander and Iber, Michael and Aigner, Wolfgang}, year = {2018}, note = {Projekt: KAVA-Time Projekt: VAST}, keywords = {FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Wiss. Beitrag, peer-reviewed}, } @article{bernard_vial_2018, title = {{VIAL} – {A} {Unified} {Process} for {Visual}-{Interactive} {Labeling}}, volume = {34}, copyright = {Springer, Berlin, Heidelberg}, issn = {1432-2315}, url = {https://bit.ly/2My1Yrt}, doi = {10/gd5hr3}, abstract = {The assignment of labels to data instances is a fundamental prerequisite for many machine learning tasks. Moreover, labeling is a frequently applied process in visual-interactive analysis approaches and visual analytics. However, the strategies for creating labels usually differ between these two fields. This raises the question whether synergies between the different approaches can be attained. In this paper, we study the process of labeling data instances with the user in the loop, from both the machine learning and visual-interactive perspective. Based on a review of differences and commonalities, we propose the ’Visual-Interactive Labeling‘ (VIAL) process that unifies both approaches. We describe the six major steps of the process and discuss their specific challenges. Additionally, we present two heterogeneous usage scenarios from the novel VIAL perspective, one on metric distance learning and one on object detection in videos. Finally, we discuss general challenges to VIAL and point out necessary work for the realization of future VIAL approaches.}, number = {1189}, journal = {The Visual Computer}, author = {Bernard, Jürgen and Zeppelzauer, Matthias and Sedlmair, Michael and Aigner, Wolfgang}, year = {2018}, note = {Projekt: KAVA-Time Projekt: IntelliGait Projekt: CARMA}, keywords = {Active Learning, Candidate Selection, Center for Artificial Intelligence, Creative Industries, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Interactive Labeling, Labeling Strategies, Machine Learning, Media Computing Group, Visual Interactive Labeling, best, best-mzeppelzauer, information visualization}, pages = {16}, } @inproceedings{bernard_jurgen_unified_2017, address = {Barcelona, Spain}, title = {A {Unified} {Process} for {Visual}-{Interactive} {Labeling}}, booktitle = {In {Proceedings} of the 8th {International} {EuroVis} {Workshop} on {Visual} {Analytics}}, author = {{Bernard, Jürgen} and {Zeppelzauer, Matthias} and {Sedlmair, Michael} and Hutter, Marco}, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Center for Artificial Intelligence, Creative Industries, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Visual analytics, Wiss. Beitrag, peer-reviewed, ⛔ No DOI found}, } @inproceedings{bernad_communities_2017, title = {Communities in biographischen {Netzwerken}}, url = {http://ceur-ws.org/Vol-2009/fmt-proceedings-2017-paper12.pdf}, abstract = {Biographical lexica are a rich data source for the Digital Humanities. For example, the connections between places can be studied based on the migrations of scholars. The work at hand resulted from the OpenGLAM.at Cultural Data Hackathon 2017 and describes the analysis of 151 biographies from the Austrian Biographical Dictionary 1815-1950. Communitiy detection algorithms were applied to find groups of places that are densely connected internally and sparsely connected between groups. The resulting communities were examined in detail using network visualization.}, booktitle = {Proceedings of the 10th {Forum} {Media} {Technology} and 3rd {All} {Around} {Audio} {Symposium}}, publisher = {CEUR-WS}, author = {Bernád, Ágoston Zénó and Kaiser, Maximilian and Mair, Sebastian M. and Rind, Alexander}, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, heritage, humanities, information visualization, network, ⛔ No DOI found}, pages = {83--87}, } @inproceedings{ceneda_guiding_2016, address = {Baltimore, MD, USA}, title = {Guiding the {Visualization} of {Time}-{Oriented} {Data}}, abstract = {The analysis of industrial processes allows quality assessment and production monitoring. Usually these operations are carried out exploiting time-series data. In this work, we analyze a concrete design study of space efficient and time-aggregating visualizations for the analysis of high-frequency time-series. We derive recommendations to enhance the design process and demonstrate their applicability to our case study.}, booktitle = {Poster {Abstracts} of {IEEE} {Conference} on {Visual} {Analytics} {Science} and {Technology} ({VAST} 2016)}, publisher = {IEEE}, author = {Ceneda, Davide and Aigner, Wolfgang and Bögl, Markus and Gschwandtner, Theresia and Miksch, Silvia}, year = {2016}, note = {Projekt: VisOnFire Projekt: KAVA-Time}, keywords = {2016, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual analytics, peer-reviewed, visualization, ⛔ No DOI found}, } @inproceedings{bogl_visual_2016, title = {Visual {Analytics} for {Time} {Series} {Model} {Selection}, {Prediction}, and {Imputation}}, url = {https://publik.tuwien.ac.at/files/PubDat_242014.pdf}, booktitle = {Extended {Abstract} at {Austrian} {Statistical} {Days}}, author = {Bögl, Markus and Aigner, Wolfgang and Filzmoser, Peter and Gschwandtner, Theresia and Lammarsch, Tim and Miksch, Silvia and Rind, Alexander}, year = {2016}, note = {Projekt: KAVA-Time}, keywords = {2016, Department Medien und Digitale Technologien, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, ⛔ No DOI found}, } @article{dahnert_looking_2019, title = {Looking beyond the horizon: {Evaluation} of four compact visualization techniques for time series in a spatial context}, shorttitle = {Looking beyond the horizon}, url = {http://arxiv.org/abs/1906.07377}, abstract = {Visualizing time series in a dense spatial context such as a geographical map is a challenging task, which requires careful balance between the amount of depicted data and perceptual precision. Horizon graphs are a well-known technique for compactly representing time series data. They provide fine details while simultaneously giving an overview of the data where extrema are emphasized. Horizon graphs compress the vertical resolution of the individual line graphs, but they do not affect the horizontal resolution. We present two variations of a new visualization technique called collapsed horizon graphs which extend the idea of horizon graphs to two dimensions. Our main contribution is a quantitative evaluation that experimentally compares four visualization techniques with high visual information resolution (compact boxplots, horizon graphs, collapsed horizon graphs, and braided collapsed horizon graphs). The experiment investigates the performance of these techniques across tasks addressing both individual graphs as well as groups of adjacent graphs. Compact boxplots consistently provide good results for all tasks, horizon graphs excel, for instance, in maximum tasks but underperform in trend detection. Collapsed horizon graphs shine in certain tasks in which an increased horizontal resolution is beneficial. Moreover, our results indicate that the visual complexity of the techniques highly affects users' confidence and perceived task difficulty.}, urldate = {2019-06-19}, journal = {arXiv:1906.07377 [cs]}, author = {Dahnert, Manuel and Rind, Alexander and Aigner, Wolfgang and Kehrer, Johannes}, year = {2019}, note = {Projekt: KAVA-Time Projekt: VisOnFire Projekt: VALID}, keywords = {FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Visual Computing, Wiss. Beitrag, ⛔ No DOI found}, } @inproceedings{aigner_kava-time_2018, title = {{KAVA}-{Time}: {Knowledge}-{Assisted} {Visual} {Analytics} {Methods} for {Time}-{Oriented} {Data}}, url = {http://ffhoarep.fh-ooe.at/handle/123456789/1070}, abstract = {Visual analytics intertwines interactive visual interfaces with automated data analysis methods in order to support humans in data analysis. How visual analytics can leverage explicit knowledge from domain experts was investigated in the basic research project KAVA-Time. Within its scope, a theoretical model for integrating the users’ knowledge into the visual analytics processes and two cases studies in the application domains IT security and clinical rehabilitation were developed.}, booktitle = {Tagungsband des 12. {Forschungsforum} der österreichischen {Fachhochschulen} ({FFH}) 2018}, author = {Aigner, Wolfgang and Rind, Alexander and Wagner, Markus}, year = {2018}, note = {Projekt: KAVA-Time}, keywords = {Center for Digital Health Innovation, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Institut für Creative Media Technologies, Visual analytics, Vortrag, Wiss. Beitrag, explicit knowledge, knowledge generation, malware analysis, peer-reviewed, ⛔ No DOI found}, } @inproceedings{wagner_knowledge-assisted_2016, address = {Vienna, Austria}, title = {Knowledge-{Assisted} {Rule} {Building} for {Malware} {Analysis}}, abstract = {Due to the increasing threat from malicious software (malware), monitoring of vulnerable systems is becoming increasingly important which includes the need to log and analyze activity encompasses networks, individual computers, as well as mobile devices. Currently available tools in behavior-based malware analysis do not meet all experts’ needs, such as selecting different rules, categorizing them by their task and storing them in the database as well as manually adapting and/or tuning of found rules. To close this gap, we designed CallNet, a knowledge-assisted visual analytics and rule building tool for behavior-based malware analysis. The paper at hand is a design study which describes the design, a usage scenario, and the paper prototype evaluation. We report on the validation of CallNet by expert reviews, reflect the gained insights of the reviews and discuss the advantages and disadvantages of the prototype design including the applied visualization techniques.}, booktitle = {Proceedings of the 10th {Forschungsforum} der oesterreichischen {Fachhochschulen}}, publisher = {FH des BFI Wien}, author = {Wagner, Markus and Rind, Alexander and Rottermanner, Gernot and Niederer, Christina and Aigner, Wolfgang}, year = {2016}, note = {Projekt: KAVA-Time}, keywords = {2016, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, peer-reviewed, ⛔ No DOI found}, } @incollection{wagner_visual_2017, title = {Visual {Analytics}: {Foundations} and {Experiences} in {Malware} {Analysis}}, isbn = {978-1-4987-7641-7}, abstract = {This chapter starts by providing some background in behavior-based malware analysis. Subsequently, it introduces VA and its main components based on the knowledge generation model for VA (Sacha et al., 2014). Then, it demonstrates the applicability of VA in in this subfield of software security with three projects that illustrate practical experience of VA methods: MalwareVis (Zhuo et al., 2012) supports network forensics and malware analysis by visually assessing TCP and DNS network streams. SEEM (Gove et al., 2014) allows visual comparison of multiple large attribute sets of malware samples, thereby enabling bulk classification. KAMAS (Wagner et al. 2017) is a knowledge-assisted visualization system for behavior-based malware forensics enabled by API calls and system call traces. Future directions in visual analytics for malware analysis conclude the chapter.}, booktitle = {Empirical {Research} for {Software} {Security}: {Foundations} and {Experience}}, publisher = {CRC/Taylor and Francis}, author = {Wagner, Markus and Sacha, Dominik and Rind, Alexander and Fischer, Fabian and Luh, Robert and Schrittwieser, Sebastian and Keim, Daniel A and Aigner, Wolfgang}, editor = {Othmane, Lotfi Ben and Jaatun, Martin Gilje and Weippl, Edgar}, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Visual Computing, Visual analytics, Wiss. Beitrag, best, best-lbwagnerm, data, interaction, knowledge generation, malware analysis, model, peer-reviewed, visualization}, pages = {139--171}, } @article{luh_sequin_2018, title = {{SEQUIN}: a grammar inference framework for analyzing malicious system behavior}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/Luh_2018_SEQUIN.pdf}, doi = {10/cwdf}, abstract = {Targeted attacks on IT systems are a rising threat to the confidentiality of sensitive data and the availability of critical systems. The emergence of Advanced Persistent Threats (APTs) made it paramount to fully understand the particulars of such attacks in order to improve or devise effective defense mechanisms. Grammar inference paired with visual analytics (VA) techniques offers a powerful foundation for the automated extraction of behavioral patterns from sequential event traces. To facilitate the interpretation and analysis of APTs, we present SEQUIN, a grammar inference system based on the Sequitur compression algorithm that constructs a context-free grammar (CFG) from string-based input data. In addition to recursive rule extraction, we expanded the procedure through automated assessment routines capable of dealing with multiple input sources and types. This automated assessment enables the accurate identification of interesting frequent or anomalous patterns in sequential corpora of arbitrary quantity and origin. On the formal side, we extended the CFG with attributes that help describe the extracted (malicious) actions. Discovery-focused pattern visualization of the output is provided by our dedicated KAMAS VA prototype.}, journal = {Journal of Computer Virology and Hacking Techniques}, author = {Luh, Robert and Schramm, Gregor and Wagner, Markus and Janicke, Helge and Schrittwieser, Sebastian}, year = {2018}, note = {Projekt: TARGET Projekt: KAVA-Time}, keywords = {FH SP Cyber Security, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Forschungsgruppe Secure Societies, Institut für Creative Media Technologies, Institut für IT Sicherheitsforschung, Josef Ressel Zentrum TARGET, Visual analytics, Wiss. Beitrag, attribute grammar, best, best-lbwagner, best-rluh, knowledge generation, malware analysis, peer-reviewed, system behavior}, pages = {01 -- 21}, } @inproceedings{rind_towards_2019, title = {Towards a {Structural} {Framework} for {Explicit} {Domain} {Knowledge} in {Visual} {Analytics}}, url = {https://arxiv.org/abs/1908.07752}, doi = {10/gh377m}, abstract = {Clinicians and other analysts working with healthcare data are in need for better support to cope with large and complex data. While an increasing number of visual analytics environments integrates explicit domain knowledge as a means to deliver a precise representation of the available data, theoretical work so far has focused on the role of knowledge in the visual analytics process. There has been little discussion about how such explicit domain knowledge can be structured in a generalized framework. This paper collects desiderata for such a structural framework, proposes how to address these desiderata based on the model of linked data, and demonstrates the applicability in a visual analytics environment for physiotherapy.}, booktitle = {Proc. {IEEE} {Workshop} on {Visual} {Analytics} in {Healthcare} ({VAHC})}, author = {Rind, Alexander and Wagner, Markus and Aigner, Wolfgang}, year = {2019}, note = {Projekt: KAVA-Time Projekt: ReMoCap-Lab}, keywords = {Center for Digital Health Innovation, Digital Health, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Visual Computing, Vortrag, Wiss. Beitrag, peer-reviewed}, pages = {33--40}, } @inproceedings{luh_sequitur-based_2017, title = {Sequitur-based {Inference} and {Analysis} {Framework} for {Malicious} {System} {Behavior}}, doi = {10/cwdb}, author = {Luh, Robert and Schramm, Georg and Wagner, Markus and Schrittwieser, Sebastian}, year = {2017}, note = {Projekt: TARGET Projekt: KAVA-Time}, keywords = {2017, Department Medien und Digitale Technologien, Department Technologie, FH SP Cyber Security, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Forschungsgruppe Secure Societies, Institut für Creative Media Technologies, Institut für IT Sicherheitsforschung, Josef Ressel Zentrum TARGET, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, peer-reviewed}, } @inproceedings{wagner_native_2016, address = {Lisbon, Portugal}, title = {Native {Cross}-platform {Visualization}: {A} {Proof} of {Concept} {Based} on the {Unity3D} {Game} {Engine}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/IV2016_UnityVis_Wagner.pdf}, doi = {10/cwc7}, abstract = {Today many different devices and operating systems can be used for InfoVis systems. On the one hand, web-based visualizations can be used to be compatible with several systems, but the performance depends on optimized browser engines. On the other hand, it is possible to build a native system which supports all the benefits for just one device. However, transferring the code to another system means parts of the code or the programming language have to be adapted. To close this gap, we present a proof of concept based on the Unity3D game engine. We implemented a prototype following the InfoVis reference model and basic interactions for interactive data exploration. A major advantage is that we have now the ability to deploy native code to over 20 different devices. Additionally, this proof of concept opens new possibilities for a future InfoVis framework which benefits from Unity3D.}, booktitle = {Proceedings of {International} {Conference} on {Information} {Visualisation} ({IV16})}, publisher = {IEEE Computer Society Press}, author = {Wagner, Markus and Blumenstein, Kerstin and Rind, Alexander and Seidl, Markus and Schmiedl, Grischa and Lammarsch, Tim and Aigner, Wolfgang}, year = {2016}, note = {Projekt: VisOnFire Projekt: KAVA-Time}, keywords = {2016, Center for Artificial Intelligence, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, peer-reviewed}, pages = {forthcoming}, } @inproceedings{bogl_visually_2015, title = {Visually and {Statistically} {Guided} {Imputation} of {Missing} {Values} in {Univariate} {Seasonal} {Time} {Series}}, url = {http://publik.tuwien.ac.at/files/PubDat_242014.pdf}, doi = {10/gh3744}, abstract = {Missing values are a problem in many real world applications, for example failing sensor measurements. For further analysis these missing values need to be imputed. Thus, imputation of such missing values is important in a wide range of applications. We propose a visually and statistically guided imputation approach, that allows applying different imputation techniques to estimate the missing values as well as evaluating and fine tuning the imputation by visual guidance. In our approach we include additional visual information about uncertainty and employ the cyclic structure of time inherent in the data. Including this cyclic structure enables visually judging the adequateness of the estimated values with respect to the uncertainty/error boundaries and according to the patterns of the neighbouring time points in linear and cyclic (e.g., the months of the year) time.}, urldate = {2015-11-19}, booktitle = {Poster {Proceedings} of the {IEEE} {Visualization} {Conference} 2015}, author = {Bögl, Markus and Filzmoser, Peter and Gschwandtner, Theresia and Miksch, Silvia and Aigner, Wolfgang and Rind, Alexander and Lammarsch, Tim}, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Statistical Analysis, Time-Oriented Data, Visual analytics, missing values, peer-reviewed, time-series, visualization}, } @inproceedings{bogl_integrating_2015, title = {Integrating {Predictions} in {Time} {Series} {Model} {Selection}}, url = {https://publik.tuwien.ac.at/files/PubDat_239076.pdf}, doi = {10/f3szvn}, abstract = {Time series appear in many different domains. The main goal in time series analysis is to find a model for given time series. The selection of time series models is done iteratively based, usually, on information criteria and residual plots. These sources may show only small variations and, therefore, it is necessary to consider the prediction capabilities in the model selection process. When applying the model and including the prediction in an interactive visual interface it is still difficult to compare deviations from actual values or benchmark models. Judging which model fits the time series adequately is not well supported in current methods. We propose to combine visual and analytical methods to integrate the prediction capabilities in the model selection process and assist in the decision for an adequate and parsimonious model. In our approach a visual interactive interface is used to select and adjust time series models, utilize the prediction capabilities of models, and compare the prediction of multiple models in relation to the actual values.}, urldate = {2015-05-28}, booktitle = {Proceedings of {theEuroVis} {Workshop} on {Visual} {Analytic}, {EuroVA}}, publisher = {Eurographics}, author = {Bögl, Markus and Aigner, Wolfgang and Filzmoser, Peter and Gschwandtner, Theresia and Lammarsch, Tim and Miksch, Silvia and Rind, Alexander}, editor = {Bertini, Enrico and Roberts, Jonathan C.}, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, peer-reviewed, visualization}, pages = {73--77}, } @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{alsallakh_state---art_2015, title = {The {State}-of-the-{Art} of {Set} {Visualization}}, volume = {Early view}, issn = {1467-8659}, url = {http://onlinelibrary.wiley.com/doi/10.1111/cgf.12722/abstract}, doi = {10/cwc5}, abstract = {Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net.}, language = {en}, urldate = {2016-01-12}, journal = {Computer Graphics Forum}, author = {Alsallakh, Bilal and Micallef, Luana and Aigner, Wolfgang and Hauser, Helwig and Miksch, Silvia and Rodgers, Peter}, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Visual Computing, Wiss. Beitrag, best, best-lbaigner, peer-reviewed, visualization}, } @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}, } @inproceedings{federico_role_2017, address = {Paolo Federico and Markus Wagner equally contributed to this paper and are both to be regarded as first authors.}, title = {The {Role} of {Explicit} {Knowledge}: {A} {Conceptual} {Model} of {Knowledge}-{Assisted} {Visual} {Analytics}}, url = {https://publik.tuwien.ac.at/files/publik_261674.pdf}, doi = {10/ghppzr}, abstract = {Visual Analytics (VA) aims to combine the strengths of humans and computers for effective data analysis. In this endeavor, humans’ tacit knowledge from prior experience is an important asset that can be leveraged by both human and computer to improve the analytic process. While VA environments are starting to include features to formalize, store, and utilize such knowledge, the mechanisms and degree in which these environments integrate explicit knowledge varies widely. Additionally, this important class of VA environments has never been elaborated on by existing work on VA theory. This paper proposes a conceptual model of Knowledge-assisted VA conceptually grounded on the visualization model by van Wijk. We apply the model to describe various examples of knowledge-assisted VA from the literature and elaborate on three of them in finer detail. Moreover, we illustrate the utilization of the model to compare different design alternatives and to evaluate existing approaches with respect to their use of knowledge. Finally, the model can inspire designers to generate novel VA environments using explicit knowledge effectively.}, booktitle = {{IEEE} {Conference} on {Visual} {Analytics} {Science} and {Technology} ({VAST})}, publisher = {IEEE}, author = {Federico, Paolo and Wagner, Markus and Rind, Alexander and Amor-Amorós, Albert and Miksch, Silvia and Aigner, Wolfgang}, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {Center for Digital Health Innovation, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Visual analytics, Vortrag, Wiss. Beitrag, automated analysis, best, best-lbaigner, explicit knowledge, information visualization, peer-reviewed, tacit knowledge, theory and model}, pages = {92--103}, } @article{stitz_thermalplot_2015, title = {{ThermalPlot}: {Visualizing} {Multi}-{Attribute} {Time}-{Series} {Data} {Using} a {Thermal} {Metaphor}}, volume = {22}, issn = {1077-2626}, url = {http://thinkh.github.io/paper-2015-thermalplot/resources/2016_thermalplot_preprint.pdf}, doi = {10/ghppzs}, abstract = {Multi-attribute time-series data plays a vital role in many different domains, such as economics, sensor networks, and biology. An important task when making sense of such data is to provide users with an overview to identify items that show an interesting development over time, including both absolute and relative changes in multiple attributes simultaneously. However, this is not well supported by existing visualization techniques. To address this issue, we present ThermalPlot, a visualization technique that summarizes combinations of multiple attributes over time using an items position, the most salient visual variable. More precisely, the x-position in the ThermalPlot is based on a user-defined degree-of-interest (DoI) function that combines multiple attributes over time. The y-position is determined by the relative change in the DoI value (DDoI) within a user-specified time window. Animating this mapping via a moving time window gives rise to circular movements of items over time—as in thermal systems. To help the user to identify important items that match user-defined temporal patterns and to increase the techniques scalability, we adapt the level of detail of the items representation based on the DoI value. Furthermore, we present an interactive exploration environment for multi-attribute time-series data that ties together a carefully chosen set of visualizations, designed to support analysts in interacting with the ThermalPlot technique. We demonstrate the effectiveness of our technique by means of two usage scenarios that address the visual analysis of economic development data and of stock market data.}, journal = {IEEE Transactions on Visualization and Computer Graphics}, author = {Stitz, Holger and Gratzl, Samuel and Aigner, Wolfgang and Streit, Marc}, year = {2015}, note = {Projekt: KAVA-Time Projekt: VisOnFire}, keywords = {Economics, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Market research, Trajectory, Visual Computing, Visualization, Wiss. Beitrag, animation, best, best-lbaigner, data visualization, encoding, focus+context, multi-attribute data, peer-reviewed, semantic zooming, time-dependent data}, pages = {2594--2607}, } @article{wagner_knowledge-assisted_2017, title = {A knowledge-assisted visual malware analysis system: design, validation, and reflection of {KAMAS}}, issn = {0167-4048}, shorttitle = {A knowledge-assisted visual malware analysis system}, url = {http://www.sciencedirect.com/science/article/pii/S0167404817300263}, doi = {10/b5j9}, abstract = {IT-security experts engage in behavior-based malware analysis in order to learn about previously unknown samples of malicious software (malware) or malware families. For this, they need to find and categorize suspicious patterns from large collections of execution traces. Currently available systems do not meet the analysts' needs which are described as: visual access suitable for complex data structures, visual representations appropriate for IT-security experts, provision of workflow-specific interaction techniques, and the ability to externalize knowledge in the form of rules to ease the analysis process and to share with colleagues. To close this gap, we designed and developed KAMAS, a knowledge-assisted visualization system for behavior-based malware analysis. This paper is a design study that describes the design, implementation, and evaluation of the prototype. We report on the validation of KAMAS with expert reviews, a user study with domain experts and focus group meetings with analysts from industry. Additionally, we reflect on the acquired insights of the design study and discuss the advantages and disadvantages of the applied visualization methods. An interesting finding is that the arc-diagram was one of the preferred visualization techniques during the design phase but did not provide the expected benefits for finding patterns. In contrast, the seemingly simple looking connection line was described as supportive in finding the link between the rule overview table and the rule detail table which are playing a central role for the analysis in KAMAS.}, number = {67}, urldate = {2017-02-17}, journal = {Computers \& Security}, author = {Wagner, Markus and Rind, Alexander and Thür, Niklas and Aigner, Wolfgang}, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Visual Computing, Visual analytics, Wiss. Beitrag, behavior-based, best, best-lbaigner, best-lbwagnerm, design study, interactive, knowledge generation, malicious software, malware analysis, peer-reviewed, prototype, visualization}, pages = {1--15}, } @article{bogl_cycle_2017, title = {Cycle {Plot} {Revisited}: {Multivariate} {Outlier} {Detection} {Using} a {Distance}-{Based} {Abstraction}}, volume = {36}, url = {http://publik.tuwien.ac.at/files/publik_260233.pdf}, doi = {10/gbnsx6}, abstract = {The cycle plot is an established and effective visualization technique for identifying and comprehending patterns in periodic time series, like trends and seasonal cycles. It also allows to visually identify and contextualize extreme values and outliers from a different perspective. Unfortunately, it is limited to univariate data. For multivariate time series, patterns that exist across several dimensions are much harder or impossible to explore. We propose a modified cycle plot using a distance-based abstraction (Mahalanobis distance) to reduce multiple dimensions to one overview dimension and retain a representation similar to the original. Utilizing this distance-based cycle plot in an interactive exploration environment, we enhance the Visual Analytics capacity of cycle plots for multivariate outlier detection. To enable interactive exploration and interpretation of outliers, we employ coordinated multiple views that juxtapose a distance-based cycle plot with Cleveland’s original cycle plots of the underlying dimensions. With our approach it is possible to judge the outlyingness regarding the seasonal cycle in multivariate periodic time series.}, journal = {Computer Graphics Forum}, author = {Bögl, Markus and Filzmoser, Peter and Gschwandtner, Theresia and Lammarsch, Tim and Leite, Roger A. and Miksch, Silvia and Rind, Alexander}, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual analytics, best, multivariate data, outlier detection, robust statistics, seasonal time series, time series}, pages = {227--238}, } @misc{aigner_media-assisted_2018, address = {Vienna}, type = {Keynote}, title = {Media-{Assisted} {Healthcare} {\textbackslash}\& {Living}: {Daten} besser nutzbar machen mit {Interaktiven} {Technologien}}, shorttitle = {{ADV} e-{Health}}, author = {Aigner, Wolfgang}, month = jun, year = {2018}, note = {Projekt: VisOnfire Projekt: KAVA-Time Projekt: CARMA Projekt: BRELOMATE Projekt: BRELOMATE2 Projekt: Umbrello Projekt: SoniGait Projekt: VisuExplore Projekt: IntelliGait Projekt: LifeStream}, keywords = {Artificial Intelligence, Center for Digital Health Innovation, Data Science, Digital Health, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Machine Learning, Visual Computing}, } @misc{aigner_visual_2018, address = {Johannes-Kepler University Linz (Austria)}, type = {Inivited talk}, title = {Visual {Analytics} as a {Design} {Science} {Discipline}}, shorttitle = {{CG} {Lab} {Talk}}, author = {Aigner, Wolfgang}, month = may, year = {2018}, note = {Projekt: CARMA Projekt: Sonigait Projekt: KAVA-Time Projekt: VALiD Projekt: VAST}, keywords = {Center for Digital Health Innovation, Data Science, Digital Health, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis, Visual Computing}, } @misc{aigner_visual_2018-1, address = {City University London (UK)}, type = {Inivited talk}, title = {Visual {Analytics} as a {Design} {Science} {Discipline}}, shorttitle = {{giCentre}}, author = {Aigner, Wolfgang}, month = may, year = {2018}, note = {Projekt: Sonigait Projekt: KAVA-Time Projekt: CARMA Projekt: VALiD Pojekt: VAST}, keywords = {Center for Digital Health Innovation, Data Science, Digital Health, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis, Visual Computing}, } @misc{aigner_visual_2018-2, address = {TU Graz (Austria)}, type = {Invited talk}, title = {Visual {Analytics} as a {Design} {Science} {Discipline}}, shorttitle = {{TU} {Graz}}, author = {Aigner, Wolfgang}, month = apr, year = {2018}, note = {Projekt: CARMA Projekt: Sonigait Projekt: KAVA-Time Projekt: VALiD Projekt: VAST}, keywords = {Center for Digital Health Innovation, Data Science, Digital Health, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis, Visual Computing}, } @misc{aigner_media-assisted_2017, address = {Krems (Austria)}, type = {Keynote}, title = {Media-{Assisted} {Healthcare} \& {Living}: {Daten} besser nutzbar machen mit {Interaktiven} {Technologien}}, shorttitle = {{HealthWeek}}, author = {Aigner, Wolfgang}, month = jun, year = {2017}, note = {Projekt: VisOnFire Projekt: KAVA-Time Projekt: BRELOMATE Projekt: BRELOMATE 2 Projekt: Umbrello Projekt: Sonigait Projekt: VisuExplore Projekt: IntelliGait Projekt: LifeStream}, keywords = {Artificial Intelligence, Center for Digital Health Innovation, Data Science, Digital Health, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Machine Learning, Visual Computing}, } @misc{aigner_visual_2016, address = {Rutgers University, USA}, type = {Invited talk}, title = {Visual {Analytics} of {Time}-{Oriented} {Data} and its {Complex} {Structures}}, shorttitle = {Rutgers}, author = {Aigner, Wolfgang}, month = oct, year = {2016}, note = {Projekt: KAVA-Time Projekt: VisOnFire}, keywords = {Data Science, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Visual Computing}, } @misc{aigner_research_2016, address = {University of Rostock, Germany}, type = {Invited {Talk}}, title = {Research {Highlights} at the {Institute} of {Creative}{\textbackslash}{Media}/{Technologies}}, shorttitle = {Rostock}, author = {Aigner, Wolfgang}, month = may, year = {2016}, note = {Projekt: KAVA-Time Projekt: VisOnFire Projekt: VALiD}, keywords = {Data Science, Digital Health, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis}, } @inproceedings{blumenstein_interactive_2015, address = {Rostock, Germany}, title = {Interactive {Data} {Visualization} for {Second} {Screen} {Applications}: {State} of the {Art} and {Technical} {Challenges}}, isbn = {978-3-8396-0960-6}, url = {https://research.fhstp.ac.at/content/download/128715/file/Blumenstein_et_al_2015_Interactive_Data_Visualization_for_Second_Screen.pdf?inLanguage=ger-DE}, abstract = {While second screen scenarios - that is, simultaneously using a phone, tablet or laptop while watching TV or a recorded broadcast - are finding their ways into the homes of millions of people, our understanding of how to properly design them is still very limited. We envision this design space and investigate how interactive data visualization can be leveraged in a second screen context. We concentrate on the state of the art in the affected areas of this topic and define technical challenges and opportunities which have to be solved for developing second screen applications including data visualization in the future.}, booktitle = {Proceedings of the {International} {Summer} {School} on {Visual} {Computing}}, publisher = {Frauenhoferverlag}, author = {Blumenstein, Kerstin and Wagner, Markus and Aigner, Wolfgang and von Suess, Rosa and Prochaska, Harald and Püringer, Julia and Zeppelzauer, Matthias and Sedlmair, Michael}, editor = {Schulz, Hans-Jörg and Urban, Bodo and Freiherr von Lukas, Uwe}, month = aug, year = {2015}, note = {Projekt: KAVA-Time Projekt: VALID}, keywords = {2015, Center for Artificial Intelligence, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Media Computing Group, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, SP MW Global Media Markets \& Local Practices, Visual analytics, Wiss. Beitrag, peer-reviewed, visualization}, pages = {35--48}, } @incollection{tominski_images_2017, title = {Images of {Time}: {Visual} {Representation} of {Time}-{Oriented} {Data}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/Tominski17ImagesOfTime.pdf}, booktitle = {Information {Design}: {Research} and {Practice}}, publisher = {Gower/Routledge}, author = {Tominski, Christian and Aigner, Wolfgang and Miksch, Silvia and Schumann, Heidrun}, editor = {Black, A. and Luna, Paul and Lund, O. and Walker, S.}, year = {2017}, note = {Projekt: VisOnFire Projekt: KAVA-Time Projekt: VALID}, keywords = {Center for Digital Health Innovation, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Visual Computing, Wiss. Beitrag, best, best-lbaigner, peer-reviewed}, pages = {23--42}, } @inproceedings{schick_supporting_2017, address = {Phoenix, Arizona, USA}, title = {Supporting {Knowledge}-assisted {Rule} {Creation} in a {Behavior}-based {Malware} {Analysis} {Prototype}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/vizsec-poster-2017.pdf}, abstract = {The ever increasing number of malicious software (malware) requires domain experts to shift their analysis process towards more individualized approaches to acquire more information about presently unknown malware samples. KAMAS is a knowledge-assisted visual analytics prototype for behavioral malware analysis, which allows IT-security experts to categorize and store potentially harmful system call sequences (rules) in a knowledge database. In order to meet the increasing demand for individualization of analysis processes, analysts have to be able to create individual rules. This paper is a visualization design study, which describes the design and implementation of a separate Rule Creation Area (RCA) into KAMAS and its evaluation by domain experts. It became clear that continuous integration of experts in interaction processes improves the analysis and knowledge generation mechanism of KAMAS. Additionally, the outcome of the evaluation revealed that there is a demand for adjustment and re-usage of already stored rules in the RCA.}, booktitle = {Poster of the 14th {Workshop} on {Visualization} for {Cyber} {Security} ({VizSec})}, author = {Schick, Johannes and Wagner, Markus and Thür, Niklas and Niederer, Christina and Rottermanner, Gernot and Tavolato, Paul and Aigner, Wolfgang}, month = oct, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Knowledge-assisted Visualization, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, User-Centered Design, Visual analytics, explicit knowledge, information visualization}, } @inproceedings{thur_big2-kamas:_2017, address = {Phoenix, Arizona, USA}, title = {{BiG2}-{KAMAS}: {Supporting} {Knowledge}-{Assisted} {Malware} {Analysis} with {Bi}-{Gram} {Based} {Valuation}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/vizsec-poster-2017%20%281%29.pdf}, abstract = {Malicious software, short malware, refers to software programs that are designed to cause damage or to perform unwanted actions on the infected computer system. The behavior-based analysis of malware typically utilizes tools that produce lengthy traces of observed events, which have to be analyzed manually or by means of individual scripts. Due to the growing amount of data extracted from malware samples, analysts are in need of an interactive tool that supports them in their exploration efforts. In this respect, the use of visual analytics methods and stored expert knowledge helps the user to speed up the exploration process and, furthermore, to improve the quality of the outcome. In this paper, the previously developed KAMAS concept is extended with components such as a bi-gram based valuation approach to cover further malware analysts’ needs. The components have been integrated a new prototype which was evaluated by two domain experts in a detailed user study.}, booktitle = {Poster of the 14th {Workshop} on {Visualization} for {Cyber} {Security} ({VizSec})}, author = {Thür, Niklas and Wagner, Markus and Schick, Johannes and Niederer, Christina and Eckel, Jürgen and Luh, Robert and Aigner, Wolfgang}, month = oct, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Knowledge-assisted Visualization, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, User-Centered Design, Visual analytics, explicit knowledge, information visualization}, } @inproceedings{thur_bigram_2017, address = {St. Pölten}, title = {A {Bigram} {Supported} {Generic} {Knowledge}-{Assisted} {Malware} {Analysis} {System}: {BiG2}-{KAMAS}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/Thuer_B2KAMAS_2017.pdf}, abstract = {Malicious software, short "malware", refers to software programs that are designed to cause damage or to perform unwanted actions on the infected computer system. Behavior-based analysis of malware typically utilizes tools that produce lengthy traces of observed events, which have to be analyzed manually or by means of individual scripts. Due to the growing amount of data extracted from malware samples, analysts are in need of an interactive tool that supports them in their exploration efforts. In this respect, the use of visual analytics methods and stored expert knowledge helps the user to speed up the exploration process and, furthermore, to improve the quality of the outcome. In this paper, the previously developed KAMAS prototype is extended with additional features such as the integration of a bi-gram based valuation approach to cover further malware analysts’ needs. The result is a new prototype which was evaluated by two domain experts in a detailed user study.}, booktitle = {Proceedings of the 10th {Forum} {Media} {Technology} 2017}, publisher = {CEUR-WS}, author = {Thür, Niklas and Wagner, Markus and Schick, Johannes and Niederer, Christina and Eckel, Jürgen and Luh, Robert and Aigner, Wolfgang}, month = nov, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Design Study, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Visual analytics, behavior-based, interactive, knowledge generation, malicious software, malware analysis, peer-reviewed, prototype, visualization}, pages = {107--115}, } @inproceedings{schick_rule_2017, address = {St. Pölten}, title = {Rule {Creation} in a {Knowledge}-assisted {Visual} {Analytics} {Prototype} for {Malware} {Analysis}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/Schick_RuleCreation_2017.pdf}, abstract = {The increasing number of malicious software (malware) requires domain experts to shift their analysis process towards more individualized approaches to acquire more information about unknown malware samples. KAMAS is a knowledge-assisted visual analytics prototype for behavioral malware analysis. It allows IT-security experts to categorize and store potentially harmful system call sequences (rules) in a knowledge database. To meet the increasing demand for individualization of analysis processes, analysts should be able to create individual rules. This paper is a visualization design study, which describes the design and implementation of a Rule Creation Area (RCA) into KAMAS and its evaluation by domain experts. It became clear that continuous integration of experts in interaction processes improves the knowledge generation mechanism of KAMAS. Additionally, the outcome of the evaluation revealed that there is a demand for adjustment and re-usage of already stored rules in the RCA.}, booktitle = {Proceedings of the 10th {Forum} {Media} {Technology} 2017}, publisher = {CEUR-WS}, author = {Schick, Johannes and Wagner, Markus and Thür, Niklas and Niederer, Christina and Rottermanner, Gernot and Tavolato, Paul and Aigner, Wolfgang}, month = nov, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Design Study, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Visual analytics, behavior-based, interactive, knowledge generation, malicious software, malware analysis, peer-reviewed, prototype, visualization}, pages = {116--123}, } @misc{rind_visual_2015, address = {CNRS, Marseille, France}, type = {Invited talk}, title = {Visual {Analytics} with a {Focus} on {Time}}, author = {Rind, Alexander}, month = jan, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Institut für Creative Media Technologies, Publikationstyp Präsentation}, } @misc{rind_visual_2015-1, address = {Pesaro, Italy}, type = {Invited talk}, title = {Visual {Analytics} of {Health} {Care} {Data} with a {Focus} on {Time}}, author = {Rind, Alexander}, month = oct, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {2015, DHC, Department Medien und Digitale Technologien, Department Technologie, Institut für Creative Media Technologies, Publikationstyp Präsentation}, } @phdthesis{wagner_integrating_2017, address = {Vienna}, type = {{PhD} {Thesis}}, title = {Integrating {Explicit} {Knowledge} in the {Visual} {Analytics} {Process}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/20170623_Dissertation_Markus_WAGNER.pdf}, abstract = {Visual analytics (VA) aims to combine the strengths of the human user and computers for effective data analysis. In this endeavor, the user’s implicit knowledge from prior experience is an important asset that can be leveraged by both, the user and the computer to improve the analytics process. While VA environments are starting to include features to formalize, store and utilize such knowledge, the mechanisms and degree to which these environments integrate explicit knowledge varies widely. Additionally, a theoretical model and formalization of this class of VA environments is not available in the VA community yet. This doctoral thesis aims to close this gap by proposing a new theoretical high-level model conceptually grounded on the ‘Simple Visualization Model’ by Van Wijk supporting the visualization community. The new ‘Knowledge-assisted VA Model’ provides the ability to describe all components and processes to characterize knowledge-assisted VA systems. Additionally, it supports visualization experts and designers by comparing and evaluating knowledge-assisted VA systems as well by creating new solutions. To demonstrate the model’s application, we use problem-driven research to study knowledge-assisted visualization systems for time-oriented data in the context of two real world problems. The first case study focuses on the domain of IT-security to support experts during behavior-based malware analysis. Therefore, we developed KAMAS, a knowledge-assisted visualization system for behavior-based malware analysis, describing its design, implementation, and evaluation. Additionally, to support clinical gait analysts during their daily work, we conducted a second case study developing KAVAGait, a knowledge-assisted VA solution for clinical gait analysis. In addition to applying the ‘Knowledge-assisted VA Model’ in two case studies, we also elaborate on two examples from literature. Moreover, we illustrated the utilization of the model for the comparison of different design alternatives and to evaluate existing approaches with respect to their use of knowledge. Our model provides the opportunity to inspire designers by using the model as a high-level blueprint to generate new VA environments using explicit knowledge effectively. Additionally, we observed that the VA process benefits in several ways by explicit knowledge: 1) by including it into the automated data analysis process; 2) for adapting the system’s specification and 3) to faster gain new implicit knowledge about the data. Finally, we present possible future directions for future research on the integration of explicit knowledge in VA.}, school = {Vienna University of Technology}, author = {Wagner, Markus}, month = jun, year = {2017}, note = {Projekt: KAVA-Time}, keywords = {2017, Extern, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, IT-security, Implicit knowledge, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual analytics, best-lbwagnerm, case studie, clinical gait analysis, explicit knowledge, information visualization, interface design, model, theory, visualization}, } @inproceedings{blumenstein_visualizing_2017, title = {Visualizing {Spatial} and {Time}-{Oriented} {Data} in a {Second} {Screen} {Application}}, abstract = {Mobile devices are more and more used in parallel, esp. in the field of TV viewing as second screen devices. Such scenarios aim to enhance the viewers’ user experience while watching TV. We designed and implemented a second screen prototype intended to be used in parallel to watching a TV documentary. It allows to interactively explore a combination of spatial and time-oriented data to extend and enrich the TV content. We evaluated our prototype in a twofold approach, consisting of expert reviews and user evaluation. We identified different interaction habits in a second screen scenario and present its benefits in relation to documentaries.}, booktitle = {Proceedings of the 19th {International} {Conference} on {Human}-{Computer} {Interaction} with {Mobile} {Devices} and {Services}}, publisher = {ACM}, author = {Blumenstein, Kerstin and Niederer, Christina and Wagner, Markus and Pfersmann, Wilhelm and Seidl, Markus and Aigner, Wolfgang}, month = sep, year = {2017}, note = {Projekt: KAVA-Time Projekt: MEETeUX Projekt: VALID}, keywords = {2017, Center for Artificial Intelligence, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, peer-reviewed}, } @misc{aigner_data_2016, address = {St. Pölten, Austria}, type = {Workshop}, title = {Data {Visualisation} in {Time}-{Based} {Media}}, url = {https://ctvkonferenz.fhstp.ac.at/}, urldate = {2016-05-16}, author = {Aigner, Wolfgang and Blumenstein, Kerstin}, month = mar, year = {2016}, note = {Projekt: KAVA-Time Projekt: VALID}, keywords = {2016, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation}, } @inproceedings{kromer_performance_2016, title = {Performance {Comparison} between {Unity} and {D3}.js for {Cross}-{Platform} {Visualization} on {Mobile} {Devices}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/Kromer_2016_FMT_crossVisComparison.pdf}, abstract = {Modern data visualizations are developed as interactive and intuitive graphic applications. In the development process, programmers basically pursue the same goal: creating an application with a great performance. Such applications have to display information at its best way in every possible situation. In this paper, we present a performance comparison on mobile devices between D3.js and Unity based on a Baby Name Explorer example. The results of the performance analysis demonstrated that Unity and D3.js are great tools for information visualization. While Unity convinced by its performance results according to our test criteria, currently Unity does not provide a visualization library.}, booktitle = {Proceedings of the 9th {Forum} {Media} {Technology} 2016}, publisher = {CEUR-WS}, author = {Kromer, Lorenz and Wagner, Markus and Blumenstein, Kerstin and Rind, Alexander and Aigner, Wolfgang}, month = nov, year = {2016}, note = {Projekt: KAVA-Time Projekt: VALID Projekt: Couragierte Gemeinde Projekt: VisOnFire}, keywords = {2016, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, peer-reviewed}, pages = {47--52}, } @inproceedings{wagner_literature_2015, title = {Literature review in visual analytics for malware pattern analysis}, abstract = {Due to the increasing number of malware, monitoring of vulnerable systems is becoming increasingly more important. This applies to networks, individual computers, as well as mobile devices. For this purpose, there are various approaches and techniques to detect or to capture malicious software. To support the analysts, visualizing the data and using visual analytics (VA) methods during data exploration are beneficial approaches. There are a number of different visualization methods available which provide interaction for data exploration. We conducted a literature survey to provide an overview of the currently existing visualization and interaction techniques for malware analysis from the view of VA. All found papers were divided into 3 main categories to present common characteristics. This report shows that the scope of malware analysis in combination with VA is still not very well explored. Many of the described approaches use only few interaction techniques and leave a lot of room for future research activities.}, booktitle = {Proceedings of the 9th {Forschungsforum} der österreichischen {Fachhochschulen}}, publisher = {FH Hagenberg}, author = {Wagner, Markus and Aigner, Wolfgang and Haberson, Andrea and Rind, Alexander}, month = apr, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {2015, Creative Industries, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, KAVA-Time, Model/Taxonomy, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Visual analytics, information visualization, malicious software, malware, peer-reviewed, visualization}, } @misc{aigner_mit_2017, address = {Göttweig (Austria)}, type = {Keynote}, title = {Mit {Visual} {Analytics} zu {Data}-{Driven} {Banking}}, shorttitle = {Bankensymp.}, author = {Aigner, Wolfgang}, month = apr, year = {2017}, note = {Projekt: KAVA-Time Projekt: VisOnFire}, keywords = {Data Science, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Visual Computing}, } @inproceedings{blumenstein_cross-platform_2015, address = {Funchal, Portugal}, title = {Cross-{Platform} {InfoVis} {Frameworks} for {Multiple} {Users}, {Screens} and {Devices}: {Requirements} and {Challenges}}, shorttitle = {Cross-{Platform} {InfoVis} {Frameworks} for {Multiple} {Users}, {Screens} and {Devices}}, booktitle = {{DEXiS} 2015 {Workshop} on {Data} {Exploration} for {Interactive} {Surfaces}. {Workshop} in conjunction wirth {ACM} {ITS}'15}, author = {Blumenstein, Kerstin and Wagner, Markus and Aigner, Wolfgang}, month = nov, year = {2015}, note = {Projekt: KAVA-Time Projekt: VALID}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, peer-reviewed, visualization}, } @inproceedings{wagner_integrating_2015, address = {Berlin}, title = {Integrating {Explicit} {Knowledge} in the {Visual} {Analytics} {Process}}, abstract = {In this paper, I describe my thesis project for the integration of explicit knowledge from domain experts into the visual analytics process. As base for the implementation of the research project, I will follow the nested model for visualization design and validation. Additionally, I use a problem-driven approach to study knowledge-assisted visualization systems for time-oriented data in the context of real world problems. At first, my research will focus on the IT-security domain where I analyze the needs of malware analysts to support them during their work. Therefore I have currently prepared a problem characterization and abstraction to understand the needs of the domain experts to gain more insight into their workflow. Based on that findings, I am currently working on the design and the implementation of a prototype. Next, I will evaluate these visual analytics methods and finally I will test the generalizability of the knowledgeassisted visual analytics methods in a second domain.}, booktitle = {Doctoral {Consortium} on {Computer} {Vision}, {Imaging} and {Computer} {Graphics} {Theory} and {Applications} ({DCVISIGRAPP} 2015)}, publisher = {SCITEPRESS Digital Library}, author = {Wagner, Markus}, month = mar, year = {2015}, note = {Projekt: KAVA-Time}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, best-lbwagnerm, peer-reviewed, visualization}, } @inproceedings{wagner_problem_2014, address = {Paris}, title = {Problem {Characterization} and {Abstraction} for {Visual} {Analytics} in {Behavior}-{Based} {Malware} {Pattern} {Analysis}}, url = {https://ifs.tuwien.ac.at/~rind/preprint/wagner_2014_VizSec_problem.pdf}, doi = {10/cv8p}, abstract = {Behavior-based analysis of emerging malware families involves finding suspicious patterns in large collections of execution traces. This activity cannot be automated for previously unknown malware families and thus malware analysts would benefit greatly from integrating visual analytics methods in their process. However existing approaches are limited to fairly static representations of data and there is no systematic characterization and abstraction of this problem domain. Therefore we performed a systematic literature study, conducted a focus group as well as semi-structured interviews with 10 malware analysts to elicit a problem abstraction along the lines of data, users, and tasks. The requirements emerging from this work can serve as basis for future design proposals to visual analytics-supported malware pattern analysis.}, booktitle = {Proceedings of the {Eleventh} {Workshop} on {Visualization} for {Cyber} {Security}}, publisher = {ACM}, author = {Wagner, Markus and Aigner, Wolfgang and Rind, Alexander and Dornhackl, Hermann and Kadletz, Konstantin and Luh, Robert and Tavolato, Paul}, editor = {Harrison, Lane}, month = nov, year = {2014}, note = {Projekt: TARGET Projekt: KAVA-Time}, keywords = {2014, Creative Industries, Department Technologie, FH SP Cyber Security, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Forschungsgruppe Secure Societies, Institut für Creative Media Technologies, Institut für IT Sicherheitsforschung, KAVA-Time, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Visual analytics, best, best-lbwagnerm, evaluation, malicious software, malware analysis, peer-reviewed, problem characterization and abstraction, user centered design, visualization}, pages = {9 -- 16}, } @inproceedings{bogl_visual_2014, title = {Visual {Analytics} {Methods} to {Guide} {Diagnostics} for {Time} {Series} {Model} {Predictions}}, url = {https://publik.tuwien.ac.at/files/PubDat_232994.pdf}, abstract = {Visual Analytics methods are used to guide domain experts in the task of model selection through an interactive visual exploration environment with short feedback cycles. Evaluation showed the benefits of this approach. However, experts also expressed the demand for prediction capabilities as being already important during the model selection process. Furthermore, good model candidates might show only small variations in the information criteria and structures which are not easily recognizable in the residual plots. To achieve this, we propose TiMoVA-Predict to close the gap and to support different types of predictions with a Visual Analytics approach. Providing prediction capabilities in addition to the information criteria and the residual plots, allows for interactively assessing the predictions during the model selection process via an visual exploration environment.}, urldate = {2022-05-24}, booktitle = {Proceedings of the {IEEE} {VIS} 2014 {Workshop} {Visualization} for {Predictive} {Analytics}, {VPA}}, author = {Bögl, Markus and Aigner, Wolfgang and Filzmoser, Peter and Gschwandtner, Theresia and Lammarsch, Tim and Miksch, Silvia and Rind, Alexander}, editor = {Perer, Adam and Bertini, Enrico and Maciejewski, Ross and Sun, Jimeng}, year = {2014}, note = {Projekt: KAVA-Time}, keywords = {Creative Industries, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, best, peer-reviewed, visualization, ⛔ No DOI found}, } @inproceedings{stitz_thermalplot_2015, address = {Chicago, IL, USA}, title = {{ThermalPlot}: {Visualizing} {Multi}-{Attribute} {Time}-{Series} {Data} {Using} a {Thermal} {Metaphor}}, url = {http://mc.fhstp.ac.at/sites/default/files/publications/Stitz%20et%20al_2015_ThermalPlot.pdf}, booktitle = {Poster {Abstracts} of {IEEE} {Conference} on {Information} {Visualization} ({InfoVis} ’15)}, publisher = {IEEE}, author = {Stitz, Holger and Gratzl, Samuel and Aigner, Wolfgang and Streit, Marc}, year = {2015}, note = {Projekt: VisOnFire Projekt: KAVA-Time Projekt: VALID}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, KAVA-Time, Poster, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Time-Oriented Data, VALiD, VisOnFire, peer-reviewed, technique, visualization, ⛔ No DOI found}, } @inproceedings{blumenstein_interactive_2015, address = {Berlin}, title = {Interactive {Mobile} {Data} {Visualization} for {Second} {Screen}}, abstract = {Traditional medial content was consumed with one device at a time. With the increasing simultaneous usage of several different devices like smartphone, tablet and connected TV new approaches for media consumption are conceivable. One specific instance is a Second Screen scenario where users complement information from unidirectional media broadcasts (i.e. TV) with additional facts from a secondary Internet connected source (e.g. smartphone or tablet). However Second Screen applications are still in its infancy and very little is known on how to properly design them. The focus in the thesis will be on the role of data visualizations and how it can be used in Second Screen application for both sides: for the viewer, allowing interactive access to additional, visual, and personalized information that is not included in the broadcast TV content; but also for the TV stations, in order to get richer data about their audience by providing a direct backchannel. By answering the research questions the complete process of designing and developing interactive data visualization in the context of Second Screen applications for mobile touch devices will be investigated. In addition to several state-of-the-art reports a tested framework, which includes all relevant parts of a Second Screen application (e.g. content creation, synchronization, different types of visualization), and guidelines for designing and developing mobile data visualization for Second Screen applications, which are synchronized with the broadcast, will be developed.}, booktitle = {Doctoral {Consortium} on {Computer} {Vision}, {Imaging} and {Computer} {Graphics} {Theory} and {Applications} ({DCVISIGRAPP} 2015)}, publisher = {SCITEPRESS Digital Library}, author = {Blumenstein, Kerstin}, year = {2015}, note = {Projekt: KAVA-Time Projekt: VALID}, keywords = {2015, AV, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, mobile computing, peer-reviewed, visualization, ⛔ No DOI found}, } @inproceedings{lammarsch_showing_2014, title = {Showing {Important} {Facts} to a {Critical} {Audience} by {Means} {Beyond} {Desktop} {Computing}}, url = {https://publik.tuwien.ac.at/files/PubDat_233657.pdf}, booktitle = {Proceedings of the {IEEE} {VIS} 2014 {Workshop} on {Envisioning} {Visualization} without {Desktop} {Computing}}, author = {Lammarsch, Tim and Aigner, Wolfgang and Miksch, Silvia and Rind, Alexander}, year = {2014}, note = {Projekt: KAVA-Time}, keywords = {Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, ⛔ No DOI found}, } @inproceedings{wagner_survey_2015, address = {Cagliari, Italy}, title = {A {Survey} of {Visualization} {Systems} for {Malware} {Analysis}}, url = {http://mc.fhstp.ac.at/supp/EuroVisStar2015}, doi = {10/cwc4}, abstract = {Due to the increasing threat from malicious software (malware), monitoring of vulnerable systems is becoming increasingly important. The need to log and analyze activity encompasses networks, individual computers, as well as mobile devices. While there are various automatic approaches and techniques available to detect, identify, or capture malware, the actual analysis of the ever-increasing number of suspicious samples is a time-consuming process for malware analysts. The use of visualization and highly interactive visual analytics systems can help to support this analysis process with respect to investigation, comparison, and summarization of malware samples. Currently, there is no survey available that reviews available visualization systems supporting this important and emerging field. We provide a systematic overview and categorization of malware visualization systems from the perspective of visual analytics. Additionally, we identify and evaluate data providers and commercial tools that produce meaningful input data for the reviewed malware visualization systems. This helps to reveal data types that are currently underrepresented, enabling new research opportunities in the visualization community.}, booktitle = {Eurographics {Conference} on {Visualization} ({EuroVis}) - {STARs}}, publisher = {The Eurographics Association}, author = {Wagner, Markus and Fischer, Fabian and Luh, Robert and Haberson, Andrea and Rind, Alexander and Keim, Daniel A. and Aigner, Wolfgang}, editor = {Borgo, Rita and Ganovelli, Fabio and Viola, Ivan}, year = {2015}, note = {Projekt: TARGET Projekt: KAVA-Time}, keywords = {Creative Industries, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Forschungsgruppe Secure Societies, Institut für Creative Media Technologies, Institut für IT Sicherheitsforschung, Josef Ressel Zentrum TARGET, KAVA-Time, Model/Taxonomy, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual Computing, Visual analytics, Vortrag, Wiss. Beitrag, best, best-lbaigner, best-lbwagnerm, best-rluh, information visualization, interdisziplinär, malicious software, malware, peer-reviewed, survey, taxonomy, visualization}, pages = {105--125}, } @article{miksch_matter_2014, title = {A {Matter} of {Time}: {Applying} a {Data}-{Users}-{Tasks} {Design} {Triangle} to {Visual} {Analytics} of {Time}-{Oriented} {Data}}, volume = {38}, url = {http://www.ifs.tuwien.ac.at/~silvia/pub/publications/miksch_cag_design-triangle-2014.pdf}, doi = {10/f3szvk}, abstract = {Increasing amounts of data offer great opportunities to promote technological progress and business success. Visual Analytics (VA) aims at enabling the exploration and the understanding of large and complex data sets by intertwining interactive visualization, data analysis, human-computer interaction, as well as cognitive and perceptual science. We propose a design triangle, which considers three main aspects to ease the design: (1) the characteristics of the data, (2) the users, and (3) the users\’ tasks. Addressing the particular characteristics of time and time-oriented data focus the VA methods, but turns the design space into a more complex and challenging one. We demonstrate the applicability of the design triangle by three use cases tackling the time-oriented aspects explicitly. Our design triangle provides a high-level framework, which is simple and very effective for the design process as well as easily applicable for both, researchers and practitioners.}, journal = {Computers \& Graphics}, author = {Miksch, Silvia and Aigner, Wolfgang}, year = {2014}, note = {Projekt: KAVA-Time {\textless}pre wrap=""{\textgreater} Available online 16 November 2013: accepted manuscript (unformatted and unedited PDF): {\textless}a class="moz-txt-link-freetext" href="http://authors.elsevier.com/sd/article/S0097849313001817"{\textgreater}http://authors.elsevier.com/sd/article/S0097849313001817{\textless}/a{\textgreater}{\textless}/pre{\textgreater}}, keywords = {Creative Industries, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Interactive Visualization, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual Computing, Visual analytics, Wiss. Beitrag, best, best-lbaigner, interaction design, peer-reviewed, temporal data mining, visualization}, pages = {286--290}, } @article{lammarsch_mind_2014, title = {Mind the {Time}: {Unleashing} {Temporal} {Aspects} in {Pattern} {Discovery}}, volume = {38}, url = {http://publik.tuwien.ac.at/files/PubDat_220406.pdf}, doi = {10/f3szvj}, abstract = {Temporal Data Mining is a core concept of Knowledge Discovery in Databases handling time-oriented data. State-of-the-art methods are capable of preserving the temporal order of events as well as the temporal intervals in between. The temporal characteristics of the events themselves, however, can likely lead to numerous uninteresting patterns found by current approaches. We present a new definition of the temporal characteristics of events and enhance related work for pattern finding by utilizing temporal relations, like meets, starts, or during, instead of just intervals between events. These prerequisites result in a new procedure for Temporal Data Mining that preserves and mines additional time-oriented information. Our procedure is supported by an interactive visual interface for exploring the patterns. Furthermore, we illustrate the effciency of our procedure presenting an benchmark of the procedure\’s run-time behavior. A usage scenario shows how the procedure can provide new insights.}, journal = {Computers \& Graphics}, author = {Lammarsch, Tim and Aigner, Wolfgang and Bertone, Alessio and Miksch, Silvia and Rind, Alexander}, editor = {Jorge, Joaquim and Schuman, Heidrun and Pohl, Margit and Schulz, Hans-Jörg}, year = {2014}, note = {{\textless}br /{\textgreater} Projekt: KAVA-Time}, keywords = {FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, KDD, Pattern Finding, Time-Oriented Data, Visual Computing, Wiss. Beitrag, best, data mining, interactive visualization, peer-reviewed, temporal data mining, visual analytics}, pages = {38--50}, } @inproceedings{rind_user_2014, series = {{BELIV} '14}, title = {User {Tasks} for {Evaluation}: {Untangling} the {Terminology} {Throughout} {Visualization} {Design} and {Development}}, isbn = {978-1-4503-3209-5}, url = {http://publik.tuwien.ac.at/files/PubDat_232654.pdf}, doi = {10/f3szvm}, abstract = {User tasks play a pivotal role in evaluation throughout visualization design and development. However, the term 'task' is used ambiguously within the visualization community. In this position paper, 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. Using these dimensions, visualization researchers can better formulate their contributions which helps advance visualization as a whole.}, booktitle = {Proceedings of the {Fifth} {Workshop} on {Beyond} {Time} and {Errors}: {Novel} {Evaluation} {Methods} for {Visualization}}, publisher = {ACM}, author = {Rind, Alexander and Aigner, Wolfgang and Wagner, Markus and Miksch, Silvia and Lammarsch, Tim}, editor = {Lam, Heidi and Isenberg, Petra and Isenberg, Tobias and Sedlmair, Michael}, year = {2014}, note = {Projekt: KAVA-Time}, keywords = {2014, Creative Industries, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Reflections, best, interaction, peer-reviewed, reflections, task taxonomy, taxonomy of tasks, terminology, visualization}, pages = {9--15}, } @inproceedings{gschwandtner_timecleanser_2014, title = {{TimeCleanser}: {A} {Visual} {Analytics} {Approach} for {Data} {Cleansing} of {Time}-{Oriented} {Data}}, isbn = {978-1-4503-2769-5}, doi = {10/ghtw5j}, abstract = {{\textless}p{\textgreater}Poor data quality leads to unreliable results of any kind of data processing and has profound economic impact. Although there are tools to help users with the task of data cleansing, support for dealing with the specifics of time-oriented data is rather poor. However, the time dimension has very specific characteristics which introduce quality problems, that are different from other kinds of data. We present TimeCleanser, an interactive Visual Analytics system to support the task of data cleansing of ime-oriented data. In order to help the user to deal with these special characteristics and quality problems, TimeCleanser combines semi-automatic quality checks, visualizations, and directly editable data tables. The evaluation of the TimeCleanser system within a focus group (two target users, one developer, and two Human Computer Interaction experts) shows that (a) our proposed method is suited to detect hidden quality problems of time-oriented data and (b) that it facilitates the complex task of data cleansing.{\textless}/p{\textgreater}}, booktitle = {14th {International} {Conference} on {Knowledge} {Technologies} and {Data}-driven {Business} (i-{KNOW} 2014)}, publisher = {ACM Press}, author = {Gschwandtner, Theresia and Aigner, Wolfgang and Miksch, Silvia and Gärtner, Johannes and Kriglstein, Simone and Pohl, Margit and Suchy, Nikolaus}, editor = {Lindstaedt, Stefanie and Granitzer, Michael and Sack, Harald}, year = {2014}, note = {Projekt: KAVA-Time}, keywords = {Creative Industries, Department Technologie, Design Study, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual analytics, best, data quality, peer-reviewed, visualization}, pages = {1--8}, } @incollection{aigner_visualization_2015, address = {Boca Raton, Florida, USA}, edition = {2nd}, title = {Visualization {Techniques} for {Time}-{Oriented} {Data}}, isbn = {978-1-4822-5737-3}, url = {https://www.crcpress.com/product/isbn/9781482257373}, booktitle = {Interactive {Data} {Visualization}: {Foundations}, {Techniques}, and {Applications}}, publisher = {A K Peters/CRC Press}, author = {Aigner, Wolfgang and Miksch, Silvia and Schumann, Heidrun and Tominski, Christian}, editor = {Ward, Matthwe O. and Grinstein, Georges and Keim, David}, year = {2015}, note = {eingeladen Projekt: KAVA-Time Projekt: VALID}, keywords = {Center for Digital Health Innovation, Creative Industries, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Time-Oriented Data, Visual Computing, Wiss. Beitrag, best, best-lbaigner, visualization}, pages = {253--284}, } @inproceedings{alsallakh_visualizing_2014, title = {Visualizing {Sets} and {Set}-typed {Data}: {State}-of-the-{Art} and {Future} {Challenges}}, url = {http://publik.tuwien.ac.at/files/PubDat_228538.pdf}, abstract = {A variety of data analysis problems can be modelled by defining multiple sets over a collection of elements and analyzing the relations between these sets. Despite their simple concept, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into 7 main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges.}, publisher = {Eurographics}, author = {Alsallakh, Bilal and Micallef, Luana and Aigner, Wolfgang and Hauser, Helwig and Miksch, Silvia and Rodgers, Peter}, editor = {Borgo, Rita and Maciejewski, Ross and Viola, Ivan}, month = jun, year = {2014}, note = {Projekt: KAVA-Time}, keywords = {Creative Industries, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, peer-reviewed, visualization}, }