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Algorithms and Complexity Artifact-based Computing and User Research Artificial Intelligence Techniques Automation Systems Business Informatics Compilers and Languages Computer Graphics Computer Vision Cyber-Physical Systems Data Science Databases and Artificial Intelligence Distributed Systems Embedded Computing Systems Formal Methods in Systems Engineering Human Computer Interaction Knowledge-Based Systems Machine Learning Parallel Computing Security and Privacy Software Engineering Theory and Logic Virtual and Augmented Reality Visual Analytics

Visual Analytics E193-07

  • A Research Unit of The Institute of Visual Computing and Human-Centered Technology

Our unit conducts research and provides teaching in Information Visualization and Visual Analytics. We are concerned with computer-tools, methods, and concepts that support humans in coping with complex information spaces.

Research Unit Visual Analytics

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Our unit conducts research and provides teaching in Information Visualization and Visual Analytics. We are concerned with computer-tools, methods, and concepts that support humans in coping with complex information spaces.

We strive to make complex information structures more comprehensible, facilitate new insights, and enable process of information and knowledge discovery. At this, human abilities as well as users’ needs and tasks are central issues to assist in situations where complex decisions need to be made. Data and information are a broad field – we focus particularly on the temporal, spatial and spatial-temporal dimension.

Visualization (Information Visualization & Visual Analytics): On the one hand, a huge amount of highly structured and unstructured data and information is available in working situations and the daily life, which need to be interpreted for further decision making. On the other hand, different kinds of data and information analysis methods have been developed to gain more insights (information and knowledge gains). We investigate interactive visual and automatic methods which support the interactive exploration process in order to gain new insights. At this, we do not primarily aim to design “beautiful pictures”, but to develop visual and automatic representations and methods to explore multidimensional information spaces, which support the shaping of hypotheses facilitated by various forms of user interactions.

Plan Management & Process Engineering: Plans, workflows, and processes are omnipresent. Computer-assisted methods could ease the handling of these. On the one hand, we develop methods to support the design of such plans and actions. On the other hand, we investigate methods to execute, adapt, and maintain these. The starting point of our research is a time-oriented, intention-based plan representation language. However, such languages are very complex and hardly accessible by the user. To overcome that situation, we study visual methods to communicate such plans (for example, metaphor graphic-based visualizations) and structure as well as model such plans in an (semi-)automatic way (for example, information extraction methods).

Bridging the Gap between Theory and Practice: Theoretical methods alone can only partly support the knowledge discovery process. Therefore, we examine the usability and applicability of our methods and apply them in the medical domain. One of our main foci is medical therapy planning:” clinical guidelines and protocols aim to support medical staff in their daily routine. Currently, guidelines and protocols are available in the form of textual documents only. However, if clinical guidelines are embedded within clinical decision support systems and integrated within the workflow of clinicians’ work habits and patient management, they could ease clinicians’ practices. Thus, they have to be presented in a structured format that can be used by clinical decision support systems. Moreover, the life cycle of such guidelines needs to be taken into account to support the concept of “living guidelines”. Other application areas are Digital Humanities, Financial Markets, Business Intelligence, Market Analysis, as well as other disciplines of Natural, Social, and Economic Science.

The research Unit Visual Analytics is part of the Institute of Visual Computing and Human-Centered Technology.

Silvia Miksch
Silvia Miksch S. Miksch

Head of Research Unit
Univ.Prof. Mag. Dr.

Alessio Arleo
Alessio Arleo A. Arleo

PostDoc Researcher
PhD

Markus Bögl
Markus Bögl M. Bögl

PostDoc Researcher
DI Dr. / BSc

Davide Ceneda
Davide Ceneda D. Ceneda

PostDoc Researcher
Dr. / BSc MSc

Velitchko Filipov
Velitchko Filipov V. Filipov

PreDoc Researcher
DI / BSc

Ignacio Baltazar Perez Messina
Ignacio Baltazar Perez Messina I. Perez Messina

PreDoc Researcher
MSc

Nikolaus Piccolotto
Nikolaus Piccolotto N. Piccolotto

PreDoc Researcher
Dipl.-Medieninf.

Stephan Bösch-Plepelits
Stephan Bösch-Plepelits S. Bösch-Plepelits

IT Services
BSc BSc

Ayu Amalia Irsyam
Ayu Amalia Irsyam A. Irsyam

Office Services
BSc

Simone Risslegger
Simone Risslegger S. Risslegger

IT Services

Natascha Zachs
Natascha Zachs N. Zachs

Office Services
BSc

2023W

 

2023

2022

  • Event‐based Dynamic Graph Drawing without the Agonizing Pain / Arleo, A., Miksch, S., & Archambault, D. (2022). Event‐based Dynamic Graph Drawing without the Agonizing Pain. Computer Graphics Forum. https://doi.org/10.1111/cgf.14615
    Download: Fulltext (1.92 MB)
  • Interactive Music Mapping Vienna: Networks In Time and Space / Filipov, V. (2022, November 18). Interactive Music Mapping Vienna: Networks In Time and Space [Conference Presentation]. VIENNA PERSPECTIVES – ART, URBAN SPACE AND SOCIAL IN-/EQUALITY, Vienna, Austria.
    Download: Slides of the presentation at the conference. (3.2 MB)
    Project: ArtVis (2022–2025)
  • Visual Analytics Meets Temporal Reasoning: Challenges and Opportunities / Miksch, S. (2022, November 8). Visual Analytics Meets Temporal Reasoning: Challenges and Opportunities [Keynote Presentation]. TIME 2022: 29th International Symposium on Temporal Representation and Reasoning, virtuel - online, Italy. https://doi.org/10.4230/LIPIcs.TIME.2022.2
  • TBSSvis: Visual analytics for temporal blind source separation / Piccolotto, N., Bögl, M., Gschwandtner, T., Muehlmann, C., Nordhausen, K., Filzmoser, P., & Miksch, S. (2022). TBSSvis: Visual analytics for temporal blind source separation. Visual Informatics, 6(4), 51–66. https://doi.org/10.1016/j.visinf.2022.10.002
  • Visual Analytics: Opportunities and Challenges / Miksch, S. (2022, October 19). Visual Analytics: Opportunities and Challenges [Conference Presentation]. VIS 2022 Panel: Grand Challenges in Visual Analytic Systems, Oklahoma City, United States of America (the).
  • Lotse: A Practical Framework for Guidance in Visual Analytics / Sperrle, F., Ceneda, D., & Mennatallah El-Assady. (2022). Lotse: A Practical Framework for Guidance in Visual Analytics. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2022.3209393
    Project: GuidedVA (2020–2024)
  • Influence Maximization with Visual Analytics / Arleo, A., Didimo, W., Liotta, G., Miksch, S., & Montecchiani, F. (2022). Influence Maximization with Visual Analytics. IEEE Transactions on Visualization and Computer Graphics, 28(10), 3428–3440. https://doi.org/10.1109/TVCG.2022.3190623
    Download: PDF (927 KB)
  • Visualization for Healthcare in the Covid-19 Era / Arleo, A. (2022, September 20). Visualization for Healthcare in the Covid-19 Era [Presentation]. Bio+Med+Vis Summer School, Brno, Czechia. http://hdl.handle.net/20.500.12708/136169
    Download: Presentation (102 MB)
  • On Time and Space: An Experimental Study on Graph Structural and Temporal Encodings / Filipov, V. (2022, September 14). On Time and Space: An Experimental Study on Graph Structural and Temporal Encodings [Conference Presentation]. Graph Drawing and Network Visualization Symposium, Tokyo, Japan.
    Projects: ArtVis (2022–2025) / KnoVA (2018–2022)
  • Visual Analytics for Blind Source Separation in Time and Space / Piccolotto, N. (2022, June 21). Visual Analytics for Blind Source Separation in Time and Space [Poster Presentation]. Austrian Computer Science Day, Klosterneuburg, Austria.
  • Visual Parameter Selection for Spatial Blind Source Separation / Piccolotto, N., Bögl, M., Mühlmann, C., Nordhausen, K., Filzmoser, P., & Miksch, S. (2022, June 15). Visual Parameter Selection for Spatial Blind Source Separation [Conference Presentation]. EuroVis 2022, Rome, Italy.
  • Show Me Your Face: Towards an Automated Method to Provide Timely Guidance in Visual Analytics / Ceneda, D., Arleo, A., Gschwandtner, T., & Miksch, S. (2022, June 14). Show Me Your Face: Towards an Automated Method to Provide Timely Guidance in Visual Analytics [Conference Presentation]. EuroVis 2022, Rom, Italy. https://doi.org/10.1109/TVCG.2021.3094870
    Download: Presentation Slides (2.48 MB)
    Projects: DoRIAH (2020–2024) / GuidedVA (2020–2024) / KnoVA (2018–2022)
  • Preface / Lee, B., Miksch, S., Ynnerman, A., Bezerianos, A., Chen, J., Chen, W., Collins, C., Gleicher, M., Gröller, E., Lex, A., Preim, B., Seo, J., Westermann, R., Yang, J., Yuan, X., Shen, H.-W., Fekete, J.-D., & Liu, S. (2022). Preface. IEEE Transactions on Visualization and Computer Graphics, 28(1), xiv–xxiii. https://doi.org/10.1109/TVCG.2021.3114891
  • Visual Parameter Selection for Spatial Blind Source Separation / Piccolotto, N., Bögl, M., Muehlmann, C., Nordhausen, K., Filzmoser, P., & Miksch, S. (2022). Visual Parameter Selection for Spatial Blind Source Separation. Computer Graphics Forum, 41(3), 157–168. https://doi.org/10.1111/cgf.14530
  • VIS 2021 - Preface / Lee, B., Miksch, S., Ynnerman, A., Bezerianos, A., Chen, J., Chen, W., Collins, C., Gleicher, M., Gröller, E., Lex, A., Preim, B., Seo, J., Westermann, R., Yang, J., Yuan, X., Shen, H. W., Fekete, J. D., & Liu, S. (2022). VIS 2021 - Preface. IEEE Transactions on Visualization and Computer Graphics, 28(1), XIV–XXIII. https://doi.org/10.1109/TVCG.2021.3114891
  • Perspectives of Visualization Onboarding and Guidance in VA / Stoiber, C., Ceneda, D., Wagner, M., Schetinger, V., Gschwandtner, T., Streit, M., Miksch, S., & Aigner, W. (2022). Perspectives of Visualization Onboarding and Guidance in VA. Visual Informatics, 6(1), 68–83. https://doi.org/10.1016/j.visinf.2022.02.005

2021

2020

2019

2018

  • Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data / Bögl, M., Bors, C., Gschwandtner, T., & Miksch, S. (2018). Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data. In A. Puig & R. Raidou (Eds.), EuroVis 2018 - Posters (pp. 45–47). The Eurographics Association. https://doi.org/10.2312/eurp.20181126
    Project: VISSECT (2016–2020)
  • Network Analysis for Financial Fraud Detection / Almeida Leite, R., Gschwandtner, T., Miksch, S., Gstrein, E., & Kuntner, J. (2018). Network Analysis for Financial Fraud Detection. In A. Puig & R. Raidou (Eds.), Proceedings of Eurographics Conference on Visualization (EuroVis 2018) (p. 3). Eurographics / VGTC. https://doi.org/10.2312/eurp.20181120
  • Sketching Temporal Uncertainty - An Exploratory User Study / Schwarzinger, F., Roschal, A., & Gschwandtner, T. (2018). Sketching Temporal Uncertainty - An Exploratory User Study. In J. Johansson, F. Sadlo, & T. Schreck (Eds.), Proceedings of the Eurographics / IEEE VGTC Conference on Visualization (EuroVis 2018). The Eurographics Association. https://doi.org/10.2312/eurovisshort.20181080
  • Guidance or No Guidance? A Decision Tree Can Help / Ceneda, D., Gschwandtner, T., May, T., Miksch, S., Streit, M., & Tominski, C. (2018). Guidance or No Guidance? A Decision Tree Can Help. In C. Tominski & T. von Landesberger (Eds.), EuroVis Workshop on Visual Analytics (EuroVA) (pp. 19–23). Eurographics Digital Library. https://doi.org/10.2312/eurova.20181107
  • Visually Exploring Data Provenance and Quality of Open Data / Bors, C., Gschwandtner, T., & Miksch, S. (2018). Visually Exploring Data Provenance and Quality of Open Data. In A. Puig & R. Raidou (Eds.), EuroVis 2018 - Posters (pp. 9–11). The Eurographics Association. https://doi.org/10.2312/eurp.20181117
  • Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series / Bernard, J., Bors, C., Bögl, M., Eichner, C., Gschwandtner, T., Miksch, S., Schumann, H., & Kohlhammer, J. (2018). Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series. In C. Tomonski & T. von Landesberger (Eds.), EuroVis Workshop on Visual Analytics (EuroVA) 2018 (pp. 49–53). Eurographics Digital Library. https://doi.org/10.2312/eurova.20181112
    Project: VISSECT (2016–2020)
  • CV3: Visual Exploration, Assessment, and Comparison of CVs / Filipov, V., Federico, P., & Miksch, S. (2018). CV3: Visual Exploration, Assessment, and Comparison of CVs. In A. Puig & R. Raidou (Eds.), EuroVis 2018 - Posters (p. 3). Eurographics / VGTC. https://doi.org/10.2312/eurp.20181115
    Project: IMMV (2017–2020)
  • Visualizing Uncertainty in Cultural Heritage Collection / Windhager, F., Filipov, V., Salisu, S., & Mayr, E. (2018). Visualizing Uncertainty in Cultural Heritage Collection. In K. Lawonn, N. N. Smit, L. Linsen, & R. Kosara (Eds.), EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3) (p. 5). Eurographics Association. https://doi.org/10.2312/eurorv3.20181142
    Project: Space-Time Cube (2016–2019)
  • Visual analytics for event detection: Focusing on fraud / Leite, R. A., Gschwandtner, T., Miksch, S., Gstrein, E., & Kuntner, J. (2018). Visual analytics for event detection: Focusing on fraud. Visual Informatics, 2(4), 198–212. https://doi.org/10.1016/j.visinf.2018.11.001
  • Viewing Visual Analytics as Model Building / Andrienko, N., Lammarsch, T., Andrienko, G., Fuchs, G., Keim, D., Miksch, S., & Rind, A. (2018). Viewing Visual Analytics as Model Building. Computer Graphics Forum, 37(6), 275–299. https://doi.org/10.1111/cgf.13324
    Project: Space-Time Cube (2016–2019)
  • EVA: Visual Analytics to Identify Fraudulent Events / Leite, R. A., Gschwandtner, T., Miksch, S., Kriglstein, S., Pohl, M., Gstrein, E., & Kuntner, J. (2018). EVA: Visual Analytics to Identify Fraudulent Events. IEEE Transactions on Visualization and Computer Graphics, 24(1), 330–339. https://doi.org/10.1109/tvcg.2017.2744758
  • Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics / Bors, C., Kriglstein, S., Gschwandtner, T., Miksch, S., & Pohl, M. (2018). Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics. Journal of Data and Information Quality, 10(1), 1–26. https://doi.org/10.1145/3190578
  • Uncertainty types in segmenting and labeling time series data / Bögl, M., Bors, C., Gschwandtner, T., & Miksch, S. (2018). Uncertainty types in segmenting and labeling time series data. Data Science, Statistics & Visualisation, Lissabon, EU. http://hdl.handle.net/20.500.12708/86861
    Project: VISSECT (2016–2020)
  • The Circle Of Thrones: Conveying the Story of Game of Thrones Using Radial Infographics / Filipov, V., Ceneda, D., Koller, M., Arleo, A., & Miksch, S. (2018). The Circle Of Thrones: Conveying the Story of Game of Thrones Using Radial Infographics. VISCOMM 2018, Berlin, Deutschland, EU. http://hdl.handle.net/20.500.12708/86757
  • Quantifying Uncertainty in Time Series Data Processing / Bors, C., Bögl, M., Bernard, J., Gschwandtner, T., & Miksch, S. (2018). Quantifying Uncertainty in Time Series Data Processing. VisInPractice Mini-Symposium on Visualizing Uncertainty, Berlin, EU. http://hdl.handle.net/20.500.12708/86740
    Project: VISSECT (2016–2020)
  • VoD - Understanding Structure, Content, and Quality of a Dataset / Peterschofsky, A., & Gschwandtner, T. (2018). VoD - Understanding Structure, Content, and Quality of a Dataset. In Proceedings of the IEEE VIS Workshop on Visual Summarization and Report Generation: Beyond Scatter-Plots and Bar-Charts (VISREG 2018). IEEE VIS Workshop on Visual Summarization and Report Generation: Beyond Scatter-Plots and Bar-Charts (VISREG 2018), Berlin, Germany, EU. IEEE Xplore Digital Library. http://hdl.handle.net/20.500.12708/57500
  • Guided Visual Exploration of Cyclical Patterns in Time-series / Ceneda, D., Gschwandtner, T., Miksch, S., & Tominski, C. (2018). Guided Visual Exploration of Cyclical Patterns in Time-series. In Visualization in Data Science. Visualization in Data Science (VDS at IEEE VIS 2018), Berlin, EU. IEEE Digital Library. http://hdl.handle.net/20.500.12708/57468
  • Know Your Enemy: Identifying Quality Problems of Time Series Data / Gschwandtner, T., & Erhart, O. (2018). Know Your Enemy: Identifying Quality Problems of Time Series Data. In 2018 IEEE Pacific Visualization Symposium (PacificVis). IEEE, Austria. IEEE Xplore Digital Library. https://doi.org/10.1109/pacificvis.2018.00034
  • Chapter 3. Exploration and Explanation in Data-Driven Storytelling / Thudt, A., Gschwandtner, T., Walny, J., Dykes, J., & Stasko, J. (2018). Chapter 3. Exploration and Explanation in Data-Driven Storytelling. In N. Henry Riche, C. Hurter, N. Diakopoulos, & S. Carpendale (Eds.), Data-Driven Storytelling (pp. 60–85). A K Peters/CRC Press. http://hdl.handle.net/20.500.12708/29731

2017

  • A Unified Process for Visual-Interactive Labeling / Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2017). A Unified Process for Visual-Interactive Labeling. In M. Sedlmair & C. Tominski (Eds.), EuroVis Workshop on Visual Analytics (EuroVA). Eurographics Association. https://doi.org/10.2312/eurova.20171123
  • Visual Analytics for Multitemporal Aerial Image Georeferencing / Amor-Amoros, A., Federico, P., Miksch, S., Zambanini, S., Brenner, S., & Sablatnig, R. (2017). Visual Analytics for Multitemporal Aerial Image Georeferencing. In M. Sedlmair & C. Tominski (Eds.), Proceedings of the EuroVis Workshop on Visual Analytics (EuroVA) (pp. 55–59). The Eurographics Association. https://doi.org/10.2312/eurova.20171120
  • A Knowledge-Assisted Visual Malware Analysis System: Design, Validation, and Reflection of KAMAS / Wagner, M., Rind, A., Thür, N., & Aigner, W. (2017). A Knowledge-Assisted Visual Malware Analysis System: Design, Validation, and Reflection of KAMAS. Computers and Security, 67, 1–15. https://doi.org/10.1016/j.cose.2017.02.003
  • Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction / Bögl, M., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Leite, R. A., Miksch, S., & Rind, A. (2017). Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction. Computer Graphics Forum, 36(3), 227–238. http://hdl.handle.net/20.500.12708/146628
    Project: VISSECT (2016–2020)
  • Characterizing Guidance in Visual Analytics / Ceneda, D., Gschwandtner, T., May, T., Miksch, S., Schulz, H.-J., Streit, M., & Tominski, C. (2017). Characterizing Guidance in Visual Analytics. IEEE Transactions on Visualization and Computer Graphics, 23(1), 111–120. https://doi.org/10.1109/tvcg.2016.2598468
  • Amending the Characterization of Guidance in Visual Analytics / Ceneda, D., Gschwandtner, T., May, T., Miksch, S., Schulz, H.-J., Streit, M., & Tominski, C. (2017). Amending the Characterization of Guidance in Visual Analytics. arXiv. https://doi.org/10.48550/arXiv.1710.06615
  • EVA: Visual Analytics to Identify Fraudulent Events / Leite, R. A., Gschwandtner, T., Miksch, S., Kriglstein, S., Pohl, M., Gstrein, E., & Kuntner, J. (2017). EVA: Visual Analytics to Identify Fraudulent Events. IEEE VIS Conference, Phoenix, AZ, USA, Non-EU. http://hdl.handle.net/20.500.12708/86534
  • Visual Support for Rastering of Unequally Spaced Time Series / Bors, C., Bögl, M., Gschwandtner, T., & Miksch, S. (2017). Visual Support for Rastering of Unequally Spaced Time Series. Data Science, Statistics & Visualisation, Lissabon, EU. http://hdl.handle.net/20.500.12708/86514
    Project: VISSECT (2016–2020)
  • Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction / Bögl, M., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Leite, R. A., Miksch, S., & Rind, A. (2017). Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction. Eurographics / IEEE VGTC Conference on Visualization (EuroVis 2017), Barcelona, Spain, EU. http://hdl.handle.net/20.500.12708/86509
    Project: VISSECT (2016–2020)
  • The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics / Federico, P., Wagner, M., Rind, A., Amor-Amoros, A., Miksch, S., & Aigner, W. (2017). The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics. In Proceedings of the IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017) (pp. 1–12). http://hdl.handle.net/20.500.12708/56998
  • Visual Analytics of Electronic Health Records with a Focus on Time / Rind, A., Federico, P., Gschwandtner, T., Aigner, W., Doppler, J., & Wagner, M. (2017). Visual Analytics of Electronic Health Records with a Focus on Time. In TELe-Health (pp. 65–77). Springer. https://doi.org/10.1007/978-3-319-28661-7_5
  • A Synoptic Visualization Framework for the Multi-Perspective Study of Biography and Prosopography Data / Windhager, F., Federico, P., Salisu, S., Schlögl, M., & Mayr, E. (2017). A Synoptic Visualization Framework for the Multi-Perspective Study of Biography and Prosopography Data. In Proceedings of the 2nd IEEE VIS Workshop on Visualization for the Digital Humanities (VIS4DH’17) (p. 5). http://hdl.handle.net/20.500.12708/56999
  • Visual support for rastering of unequally spaced time series / Bors, C., Bögl, M., Gschwandtner, T., & Miksch, S. (2017). Visual support for rastering of unequally spaced time series. In R. P. Biuk-Aghai, J. Li, & S. Takahashi (Eds.), Proceedings of the 10th International Symposium on Visual Information Communication and Interaction. ACM International Conference Proceeding Series. https://doi.org/10.1145/3105971.3105984
    Project: VISSECT (2016–2020)
  • Visual Analytics Meets Process Mining: Challenges and Opportunities / Gschwandtner, T. (2017). Visual Analytics Meets Process Mining: Challenges and Opportunities. In S. Rinderle-Ma & P. Ceravolo (Eds.), Post Proceeding of the Fifth International Symposium on Data-Driven Process Discovery and Analysis (p. 13). Springer. http://hdl.handle.net/20.500.12708/56611
  • Images of Time: Visual Representation of Time-Oriented Data / Tominski, C., Aigner, W., Miksch, S., & Schumann, H. (2017). Images of Time: Visual Representation of Time-Oriented Data. In Information Design: Research and Practice (pp. 23–42). Routledge. http://hdl.handle.net/20.500.12708/29672

2016

  • Visual-Interactive Segmentation of Multivariate Time Series / Bernard, J., Dobermann, E., Bögl, M., Röhlig, M., Vögele, A., & Kohlhammer, J. (2016). Visual-Interactive Segmentation of Multivariate Time Series. In N. Andrienko & M. Sedlmair (Eds.), EuroVA 2016 EuroVis Workshop on Visual Analytics (pp. 31–35). The Eurographics Association. https://doi.org/10.2312/eurova.20161121
    Project: VISSECT (2016–2020)
  • The State-of-the-Art of Set Visualization / Alsallakh, B., Micallef, L., Aigner, W., Hauser, H., Miksch, S., & Rodgers, P. (2016). The State-of-the-Art of Set Visualization. Computer Graphics Forum, 35(1), 234–260. http://hdl.handle.net/20.500.12708/150103
  • A Survey on Visual Approaches for Analyzing Scientific Literature and Patents / Federico, P., Heimerl, F., Koch, S., & Miksch, S. (2016). A Survey on Visual Approaches for Analyzing Scientific Literature and Patents. IEEE Transactions on Visualization and Computer Graphics, 23(9), 2179–2198. https://doi.org/10.1109/tvcg.2016.2610422
    Project: EXPAND (2012–2016)
  • Visual Encodings of Temporal Uncertainty: A Comparative User Study / Gschwandtner, T., Bögl, M., Federico, P., & Miksch, S. (2016). Visual Encodings of Temporal Uncertainty: A Comparative User Study. IEEE Transactions on Visualization and Computer Graphics, 22(1), 539–548. https://doi.org/10.1109/tvcg.2015.2467752
  • Characterizing Guidance in Visual Analytics / Ceneda, D., Gschwandtner, T., May, T., Miksch, S., Schulz, H.-J., Streit, M., & Tominski, C. (2016). Characterizing Guidance in Visual Analytics (p. 120). http://hdl.handle.net/20.500.12708/86330
  • Exploring Media Transparency With Multiple Views / Rind, A., Pfahler, D., Niederer, C., & Aigner, W. (2016). Exploring Media Transparency With Multiple Views. In Proceedings of the 9th Forum Media Technology 2016 (pp. 65–73). CEUR-WS.org. http://hdl.handle.net/20.500.12708/56612
  • Visual Analytics for Fraud Detection: Focusing on Profile Analysis / Almeida Leite, R., Gschwandtner, T., Miksch, S., Gstrein, E., & Kuntner, J. (2016). Visual Analytics for Fraud Detection: Focusing on Profile Analysis. In T. Isenberg & F. Sadlo (Eds.), Poster proceedings of Eurographics Conference on Visualization (EuroVis 2016) (p. 3). http://hdl.handle.net/20.500.12708/56485
  • Reframing Cultural Heritage Collections in a Visualization Framework of Space-Time Cubes / Windhager, F., Mayr, E., Schreder, G., Smuc, M., Federico, P., & Miksch, S. (2016). Reframing Cultural Heritage Collections in a Visualization Framework of Space-Time Cubes. In Proceedings of the 3rd HistoInformatics Workshop on Computational History (HistoInformatics 2016), (pp. 20–24). CEUR-WS. http://hdl.handle.net/20.500.12708/55430
    Project: Space-Time Cube (2016–2019)
  • A Review of Information Visualization Approaches and Interfaces to Digital Cultural Heritage Collections / Windhager, F., Federico, P., Mayr, E., Schreder, G., & Smuc, M. (2016). A Review of Information Visualization Approaches and Interfaces to Digital Cultural Heritage Collections. In Proceedings of the 9th Forum Media Technology (FMT2016) (pp. 74–81). St. Pölten University of Applied Sciences, Institute of Creative\Media/Technologies. http://hdl.handle.net/20.500.12708/56893
    Project: Space-Time Cube (2016–2019)
  • Guiding the Visualization of Time-oriented Data / Ceneda, D., Aigner, W., Bögl, M., Gschwandtner, T., & Miksch, S. (2016). Guiding the Visualization of Time-oriented Data. In Proceedings of IEEE VIS. IEEE Visualization, Minneapolis, USA, Austria. http://hdl.handle.net/20.500.12708/56578
  • Visually-supported graph traversals for exploratory analysis / Amor-Amoros, A., Federico, P., & Miksch, S. (2016). Visually-supported graph traversals for exploratory analysis. In Proceedings of IEEE VIS (p. 2). http://hdl.handle.net/20.500.12708/56552
    Project: EXPAND (2012–2016)
  • A Nested Workflow Model for Visual Analytics Design and Validation / Federico, P., Amor-Amorós, A., & Miksch, S. (2016). A Nested Workflow Model for Visual Analytics Design and Validation. In Proceedings of the Beyond Time and Errors on Novel Evaluation Methods for Visualization - BELIV ’16. Sixth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualisation (BELIV ´16), Baltimore, MD, USA, Non-EU. ACM. https://doi.org/10.1145/2993901.2993915
    Project: DeVisOR (2015–2017)
  • Evaluation of Two Interaction Techniques for Visualization of Dynamic Graphs / Federico, P., & Miksch, S. (2016). Evaluation of Two Interaction Techniques for Visualization of Dynamic Graphs. In Lecture Notes in Computer Science (pp. 557–571). Springer. https://doi.org/10.1007/978-3-319-50106-2_43
    Project: EXPAND (2012–2016)
  • Visualization of Cultural Heritage Data for Casual Users / Mayr, E., Federico, P., Miksch, S., Schreder, G., Smuc, M., & Windhager, F. (2016). Visualization of Cultural Heritage Data for Casual Users. In Workshop on Visualization for the Digital Humanities (p. 4). http://hdl.handle.net/20.500.12708/56535
    Project: Space-Time Cube (2016–2019)

2015

  • A Survey of Visualization Systems for Malware Analysis / Wagner, M., Fischer, F., Luh, R., Haberson, A., Rind, A., Keim, D., & Aigner, W. (2015). A Survey of Visualization Systems for Malware Analysis. In R. Borgo, F. Ganovelli, & I. Viola (Eds.), Eurographics Conference on Visualization (EuroVis) State of The Art Reports (pp. 105–125). EuroGraphics. https://doi.org/10.2312/eurovisstar.20151114
  • Vials: Visualizing Alternative Splicing of Genes / Strobelt, H., Alsallakh, B., Botros, J., Peterson, B., Borowsky, M., Pfister, H., & Lex, A. (2015). Vials: Visualizing Alternative Splicing of Genes. IEEE Transactions on Visualization and Computer Graphics, 22(1), 399–408. https://doi.org/10.1109/tvcg.2015.2467911
  • Task Cube: A Three-Dimensional Conceptual Space of User Tasks in Visualization Design and Evaluation / Rind, A., Aigner, W., Wagner, M., Miksch, S., & Lammarsch, T. (2015). Task Cube: A Three-Dimensional Conceptual Space of User Tasks in Visualization Design and Evaluation. Information Visualization, 15(4), 288–300. https://doi.org/10.1177/1473871615621602
    Project: HypoVis (2011–2015)
  • Exploration and Assessment of Event Data / Bodesinsky, P., Alsallakh, B., Gschwandtner, T., & Miksch, S. (2015). Exploration and Assessment of Event Data. In E. Bertini & J. C. Roberts (Eds.), EuroVA 2015 EuroVis Workshop on Visual Analytics (pp. 67–71). The Eurographics Association. https://doi.org/10.2312/eurova.20151106
  • Gnaeus: utilizing clinical guidelines for a knowledge-assisted visualisation of EHR cohorts / Federico, P., Unger, J., Amor-Amoros, A., Sacchi, L., Klimov, D., & Miksch, S. (2015). Gnaeus: utilizing clinical guidelines for a knowledge-assisted visualisation of EHR cohorts. In E. Bertini & J. C. Roberts (Eds.), EuroVA 2015 EuroVis Workshop on Visual Analytics (pp. 79–83). The Eurographics Association. https://doi.org/10.2312/eurova.20151108
    Project: MobiGuide (2011–2015)
  • Integrating Predictions in Time Series Model Selection / Bögl, M., Aigner, W., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Miksch, S., & Rind, A. (2015). Integrating Predictions in Time Series Model Selection. In J. Yang, E. Bertini, N. Elmqvist, T. Dwyer, X. Yuan, & H. Carr (Eds.), EuroVA 2015 EuroVis Workshop on Visual Analytics (pp. 73–78). The Eurographics Association. https://doi.org/10.2312/eurova.20151107
    Project: HypoVis (2011–2015)
  • Visual Analytics Meets Process Mining: Challenges and Opportunities / Gschwandtner, T., & Miksch, S. (2015). Visual Analytics Meets Process Mining: Challenges and Opportunities. Fifth International Symposium on Data-Driven Process Discovery and Analysis, Wien, Austria. http://hdl.handle.net/20.500.12708/86356
  • Visually and Statistically Guided Imputation of Missing Values in Univariate Seasonal Time Series / Bögl, M., Aigner, W., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Miksch, S., & Rind, A. (2015). Visually and Statistically Guided Imputation of Missing Values in Univariate Seasonal Time Series. In J. Yang, E. Bertini, N. Elmqvist, T. Dwyer, X. Yuan, & H. Carr (Eds.), Poster Proceedings of the IEEE Visualization Conference 2015 (p. 2). http://hdl.handle.net/20.500.12708/56130
  • Visual Analytics for Fraud Detection and Monitoring / Almeida Leite, R., Gschwandtner, T., Miksch, S., Gstrein, E., & Kuntner, J. (2015). Visual Analytics for Fraud Detection and Monitoring. In J. Yang, E. Bertini, N. Elmqvist, T. Dwyer, X. Yuan, & H. Carr (Eds.), Poster Proceedings of the IEEE Visualization Conference 2015 (p. 2). http://hdl.handle.net/20.500.12708/56390
  • Supporting Activity Recognition by Visual Analytics / Röhlig, M., Luboschik, M., Bögl, M., Krüger, F., Alsallakh, B., Miksch, S., Kirste, T., & Schumann, H. (2015). Supporting Activity Recognition by Visual Analytics. In Proceedings of the IEEE Conference on Visual Analytics Science and Technology (p. 8). IEEE. http://hdl.handle.net/20.500.12708/56131
  • QualityFlow: Provenance Generation from Data Quality / Bors, C., Gschwandtner, T., & Miksch, S. (2015). QualityFlow: Provenance Generation from Data Quality. In R. Maciejewski & F. Marton (Eds.), Proceedings of the Eurographics Conference on Visualization (EuroVis) - Posters 2015 (p. 3). Eurographics Association. http://hdl.handle.net/20.500.12708/56051
  • Enhancing Time Series Segmentation and Labeling Through the Knowledge Generation Model / Gschwandtner, T., Schumann, H., Bernard, J., May, T., Bögl, M., Miksch, S., Kohlhammer, J., Röhlig, M., & Alsallakh, B. (2015). Enhancing Time Series Segmentation and Labeling Through the Knowledge Generation Model. In R. Maciejewski & F. Marton (Eds.), Proceedings of the Eurographics Conference on Visualization (EuroVis) - Posters 2015 (p. 3). Eurographics Association. http://hdl.handle.net/20.500.12708/56049
  • A Concept for the Exploratory Visualization of Patent Network Dynamics / Windhager, F., Amor-Amorós, A., Smuc, M., Federico, P., Zenk, L., & Miksch, S. (2015). A Concept for the Exploratory Visualization of Patent Network Dynamics. In Proceedings of the 6th International Conference on Information Visualization Theory and Applications. The International Conference on Information Visualization Theory and Applications IVAPP, Berlin, EU. https://doi.org/10.5220/0005360002680273
    Project: EXPAND (2012–2016)
  • Visual Exploration and Analysis of Uncertain Time-oriented Data / Bögl, M. (2015). Visual Exploration and Analysis of Uncertain Time-oriented Data. In E. Marai, C. Collins, & M. Pohl (Eds.), Proceedings of the IEEE VIS 2015 Doctoral Colloquium - closed, invitation only special session (p. 4). http://hdl.handle.net/20.500.12708/56037
  • Visualization Techniques for Time-Oriented Data / Aigner, W., Miksch, S., Schumann, H., & Tominski, C. (2015). Visualization Techniques for Time-Oriented Data. In Interactive Data Visualization: Foundations, Techniques, and Applications, 2nd edition (pp. 253–284). A K Peters/CRC Press. http://hdl.handle.net/20.500.12708/28671

2014

  • Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges / Alsallakh, B., Micallef, L., Aigner, W., Hauser, H., Miksch, S., & Rodgers, P. (2014). Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges. In R. Borgo, R. Maciejewski, & I. Viola (Eds.), Eurographics Conference on Visualization - State of The Art Reports (pp. 1–21). Eurographics. https://doi.org/10.2312/eurovisstar.20141170
  • A Visual Analytics Approach to Segmenting and Labeling Multivariate Time Series Data / Alsallakh, B., Bögl, M., Gschwandtner, T., Miksch, S., Esmael, B., Arnaout, A., Thonhauser, G., & Zöllner, P. (2014). A Visual Analytics Approach to Segmenting and Labeling Multivariate Time Series Data. In M. Pohl & J. C. Roberts (Eds.), EuroVis Workshop on Visual Analytics (EuroVA) (pp. 31–35). Eurographics. https://doi.org/10.2312/eurova.20141142
  • A Matter of Time: Applying a Data-Users-Tasks Design Triangle to Visual Analytics of Time-Oriented Data / Miksch, S., & Aigner, W. (2014). A Matter of Time: Applying a Data-Users-Tasks Design Triangle to Visual Analytics of Time-Oriented Data. Computers and Graphics, 38, 286–290. https://doi.org/10.1016/j.cag.2013.11.002
    Projects: HypoVis (2011–2015) / VIENA (2011–2013)
  • Visual Methods for Analyzing Probabilistic Classification Data / Alsallakh, B., Hanbury, A., Hauser, H., Miksch, S., & Rauber, A. (2014). Visual Methods for Analyzing Probabilistic Classification Data. IEEE Transactions on Visualization and Computer Graphics, 20(12), 1703–1712. https://doi.org/10.1109/tvcg.2014.2346660
  • Mind the Time: Unleashing Temporal Aspects in Pattern Discovery / Lammarsch, T., Aigner, W., Miksch, S., Bertone, A., & Rind, A. (2014). Mind the Time: Unleashing Temporal Aspects in Pattern Discovery. Computers and Graphics, 38, 38–50. https://doi.org/10.1016/j.cag.2013.10.007
    Project: HypoVis (2011–2015)
  • Evaluating the Dot-Based Contingency Wheel: Results from a Usability and Utility Study / Pohl, M., Scholz, F., Kriglstein, S., Alsallakh, B., & Miksch, S. (2014). Evaluating the Dot-Based Contingency Wheel: Results from a Usability and Utility Study. In S. Yamamoto (Ed.), Human Interface and the Management of Information. Information and Knowledge Design and Evaluation (pp. 76–86). Springer. https://doi.org/10.1007/978-3-319-07731-4_8
  • Knowledge-assisted EHR visualization for cohorts / Federico, P., Amor-Amoros, A., & Miksch, S. (2014). Knowledge-assisted EHR visualization for cohorts. Workshop on Visualizing Electronic Health Record Data (EHRVis 2014), Paris, EU. http://hdl.handle.net/20.500.12708/85881
    Project: MobiGuide (2011–2015)
  • Knowledge Representation for Health Care / Miksch, S., Riano, D., & ten Teije, A. (Eds.). (2014). Knowledge Representation for Health Care. Springer International Publishing. https://doi.org/10.1007/978-3-319-13281-5
    Project: MobiGuide (2011–2015)
  • Showing Important Facts to a Critical Audience by Means Beyond Desktop Computing / Lammarsch, T., Aigner, W., Miksch, S., & Rind, A. (2014). Showing Important Facts to a Critical Audience by Means Beyond Desktop Computing. In Y. Jansen, P. Isenberg, J. Dykes, S. Carpendale, & D. Keefe (Eds.), Death of the Desktop - Envisioning Visualization without Desktop Computing. http://hdl.handle.net/20.500.12708/55768
    Project: HypoVis (2011–2015)
  • QualityTrails: Data Quality Provenance as a Basis for Sensemaking / Bors, C., Gschwandtner, T., Miksch, S., & Gärtner, J. (2014). QualityTrails: Data Quality Provenance as a Basis for Sensemaking. In K. Xu, S. Attfield, & T. J. Jankun-Kelly (Eds.), Proceedings of the IEEE VIS Workshop on Provenance for Sensemaking (pp. 1–2). http://hdl.handle.net/20.500.12708/55302
  • User tasks for evaluation / Rind, A., Aigner, W., Wagner, M., Miksch, S., & Lammarsch, T. (2014). User tasks for evaluation. In Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization. Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV 2014), Paris, Frankreich, EU. ACM digital library. https://doi.org/10.1145/2669557.2669568
  • Experiences and Challenges with Evaluation Methods in Practice: A Case Study / Kriglstein, S., Pohl, M., Suchy, N., Gärtner, J., Gschwandtner, T., & Miksch, S. (2014). Experiences and Challenges with Evaluation Methods in Practice: A Case Study. In Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV 2014) (pp. 118–125). ACM digital library. http://hdl.handle.net/20.500.12708/55292
  • TimeCleanser / Gschwandtner, T., Aigner, W., Miksch, S., Gärtner, J., Kriglstein, S., Pohl, M., & Suchy, N. (2014). TimeCleanser. In S. Lindstaedt, M. Granitzer, & H. Sack (Eds.), Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business - i-KNOW ’14. ACM Press. https://doi.org/10.1145/2637748.2638423
  • Analyzing Parameter Influence on Time-Series Segmentation and Labeling / Röhlig, M., Luboschik, M., Schumann, H., Bögl, M., Alsallakh, B., & Miksch, S. (2014). Analyzing Parameter Influence on Time-Series Segmentation and Labeling. In G. Andrienko, E. Bertini, H. Carr, N. Elmqvist, B. Lee, & H. Leitte (Eds.), Poster Proceedings of the IEEE Visualization Conference 2014. http://hdl.handle.net/20.500.12708/55193
  • TimeGraph: a data management framework for Visual Analytics of large multivariate time-oriented networks / Amor-Amoros, A., Federico, P., & Miksch, S. (2014). TimeGraph: a data management framework for Visual Analytics of large multivariate time-oriented networks. In Poster Proceedings of the IEEE Visualization Conference 2014. IEEE Visualization, Minneapolis, USA, Austria. http://hdl.handle.net/20.500.12708/55158
    Project: EXPAND (2012–2016)
  • Towards a Visualization of Multi-faceted Search Results / Alsallakh, B., Miksch, S., & Rauber, A. (2014). Towards a Visualization of Multi-faceted Search Results. In Workshop on Knowledge Maps and Information Retrieval (KMIR). Workshop on Knowledge Maps and Information Retrieval (KMIR), at the the ACM/IEEE Joint Conference on Digital Libraries, London, EU. http://hdl.handle.net/20.500.12708/55156
  • Visual Analytics Methods to Guide Diagnostics for Time Series Model Predictions / Bögl, M., Aigner, W., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Miksch, S., & Rind, A. (2014). Visual Analytics Methods to Guide Diagnostics for Time Series Model Predictions. In Proceedings of the 2014 IEEE VIS Workshop on Visualization for Predictive Analytics (p. 4). http://hdl.handle.net/20.500.12708/55730
  • Visual Process Mining: Event Data Exploration and Analysis / Bodesinsky, P., Alsallakh, B., Gschwandtner, T., & Miksch, S. (2014). Visual Process Mining: Event Data Exploration and Analysis. In G. Andrienko, E. Bertini, H. Carr, N. Elmqvist, B. Lee, & H. Leitte (Eds.), VAST Poster Proceedings of the IEEE Visualization Conference (VIS 2014) (p. 2). http://hdl.handle.net/20.500.12708/55817
  • Qualizon graphs / Federico, P., Hoffmann, S., Rind, A., Aigner, W., & Miksch, S. (2014). Qualizon graphs. In Proceedings of the 2014 International Working Conference on Advanced Visual Interfaces - AVI ’14. 12th International Working Conference on Advanced Visual Interfaces (AVI2014), Como (Italy), EU. ACM. https://doi.org/10.1145/2598153.2598172
    Project: MobiGuide (2011–2015)
  • Temporal Multivariate Networks / Archambault, D., Abello, J., Kennedy, J., Kobourov, S., Ma, K.-L., Miksch, S., Muelder, C., & Telea, A. C. (2014). Temporal Multivariate Networks. In Multivariate Network Visualization (pp. 151–174). Springer. https://doi.org/10.1007/978-3-319-06793-3_8
    Project: EXPAND (2012–2016)

2013

  • Mind the Time: Unleashing the Temporal Aspects in Pattern Discovery / Lammarsch, T., Aigner, W., Bertone, A., Miksch, S., & Rind, A. (2013). Mind the Time: Unleashing the Temporal Aspects in Pattern Discovery. In M. Pohl & H. Schumann (Eds.), Proceedings of the Fourth International EuroVis Workshop on Visual Analytics held in Europe (EuroVA 2013) (pp. 31–35). Eurographics Publications. https://doi.org/10.2312/PE.EuroVAST.EuroVA13.031-035
    Project: HypoVis (2011–2015)
  • TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data / Rind, A., Lammarsch, T., Aigner, W., Alsallakh, B., & Miksch, S. (2013). TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2247–2256. https://doi.org/10.1109/tvcg.2013.206
    Project: HypoVis (2011–2015)
  • Radial Sets: Interactive Visual Analysis of Large Overlapping Sets / Alsallakh, B., Aigner, W., Miksch, S., & Hauser, H. (2013). Radial Sets: Interactive Visual Analysis of Large Overlapping Sets. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2496–2505. https://doi.org/10.1109/tvcg.2013.184
  • EvalBench: A Software Library for Visualization Evaluation / Aigner, W., Hoffmann, S., & Rind, A. (2013). EvalBench: A Software Library for Visualization Evaluation. Computer Graphics Forum, 32(3), 41–50. http://hdl.handle.net/20.500.12708/154847
    Projects: EXPAND (2012–2016) / HypoVis (2011–2015) / MobiGuide (2011–2015)
  • Interactive Information Visualization to Explore and Query Electronic Health Records / Rind, A., Wang, T. D., Aigner, W., Miksch, S., Wongsuphasawat, K., Plaisant, C., & Shneiderman, B. (2013). Interactive Information Visualization to Explore and Query Electronic Health Records. Foundations and Trends in Human-Computer Interaction, 5(3), 207–298. https://doi.org/10.1561/1100000039
    Project: HypoVis (2011–2015)
  • On Visualizing Knowledge Flows at a University Department / Windhager, F., Smuc, M., Zenk, L., Federico, P., Pfeffer, J., & Aigner, W. (2013). On Visualizing Knowledge Flows at a University Department. Procedia - Social and Behavioral Sciences, 100, 127–143. https://doi.org/10.1016/j.sbspro.2013.10.704
    Project: VIENA (2011–2013)
  • Visual Analytics for Model Selection in Time Series Analysis / Bögl, M., Aigner, W., Filzmoser, P., Lammarsch, T., Miksch, S., & Rind, A. (2013). Visual Analytics for Model Selection in Time Series Analysis. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2237–2246. https://doi.org/10.1109/tvcg.2013.222
    Project: HypoVis (2011–2015)
  • State-of-the-art methods for visualizing set-typed data / Alsallakh, B. (2013). State-of-the-art methods for visualizing set-typed data. Seminar of the Computational Intelligence Group, University of Kent, Canterbury, EU. http://hdl.handle.net/20.500.12708/85660
  • Radial Sets: Interactive Visual Analysis of Large Overlapping Sets / Alsallakh, B., Aigner, W., Miksch, S., & Hauser, H. (2013). Radial Sets: Interactive Visual Analysis of Large Overlapping Sets. IEEE Conference on Information Visualization (InfoVis 2013), Atlanta, Non-EU. http://hdl.handle.net/20.500.12708/85612
  • Visual Analytics for Model Selection in Time Series Analysis / Bögl, M., Aigner, W., Filzmoser, P., Lammarsch, T., Miksch, S., & Rind, A. (2013). Visual Analytics for Model Selection in Time Series Analysis. IEEE Conference on Visual Analytics Science and Technology (IEEE VAST), Atlanta, GA, USA, Non-EU. http://hdl.handle.net/20.500.12708/85611
    Project: HypoVis (2011–2015)
  • TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data / Rind, A., Lammarsch, T., Aigner, W., Alsallakh, B., & Miksch, S. (2013). TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data. IEEE Conference on Visual Analytics Science and Technology (IEEE VAST), Atlanta, GA, USA, Non-EU. http://hdl.handle.net/20.500.12708/85606
    Project: HypoVis (2011–2015)
  • Hobbit - The Mutual Care Robot / Fischinger, D., Einramhof, P., Wohlkinger, W., Papoutsakis, K., Mayer, P., Panek, P., Koertner, T., Hoffmann, S., Argyros, A., Vincze, M., Gisinger, C., & Weiss, A. (2013). Hobbit - The Mutual Care Robot. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013) (p. 6). http://hdl.handle.net/20.500.12708/73759
  • Visual Analysis of Compliance with Clinical Guidelines / Bodesinsky, P., Federico, P., & Miksch, S. (2013). Visual Analysis of Compliance with Clinical Guidelines. In Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies - i-Know ’13. 13th International Conference on Knowledge Management and Knowledge Technologies (i-KNOW), Graz, Austria. ACM. https://doi.org/10.1145/2494188.2494202
    Project: MobiGuide (2011–2015)
  • Current Work Practice and Users' Perspectives on Visualization and Interactivity in Business Intelligence / Aigner, W. (2013). Current Work Practice and Users’ Perspectives on Visualization and Interactivity in Business Intelligence. In 2013 17th International Conference on Information Visualisation. IEEE Computer Society Press. https://doi.org/10.1109/iv.2013.38
  • Supporting Computer-Interpretable Guidelines' Modeling by Automatically Classifying Clinical Actions / Minard, A.-L., & Kaiser, K. (2013). Supporting Computer-Interpretable Guidelines’ Modeling by Automatically Classifying Clinical Actions. In D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, & A. ten Teije (Eds.), Proceedings of the Joint International Workshop: 5th Knowledge Representation for Health Care (KR4HC’13) + 6th Process-Oriented Information Systems in Healthcare (ProHealth’13) (pp. 30–44). http://hdl.handle.net/20.500.12708/54645
    Projects: Brigid (2010–2015) / MobiGuide (2011–2015)
  • Identifying Condition-Action Sentences Using a Heuristic-based Information Extraction Method / Wenzina, R., & Kaiser, K. (2013). Identifying Condition-Action Sentences Using a Heuristic-based Information Extraction Method. In D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, & A. ten Teije (Eds.), Proceedings of the Joint International Workshop: 5th Knowledge Representation for Health Care (KR4HC’13) + 6th Process-Oriented Information Systems in Healthcare (ProHealth’13) (pp. 17–29). http://hdl.handle.net/20.500.12708/54644
    Project: Brigid (2010–2015)
  • Interactive Visual Transformation for Symbolic Representation of Time-Oriented Data / Lammarsch, T., Aigner, W., Bertone, A., Bögl, M., Gschwandtner, T., Miksch, S., & Rind, A. (2013). Interactive Visual Transformation for Symbolic Representation of Time-Oriented Data. In A. Holzinger, M. Ziefle, & V. Glavinić (Eds.), Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data (pp. 400–419). Springer. https://doi.org/10.1007/978-3-642-39146-0_37
  • Visualizing Complex Process Hierarchies During the Modeling Process / Seyfang, A., Kaiser, K., Gschwandtner, T., & Miksch, S. (2013). Visualizing Complex Process Hierarchies During the Modeling Process. In M. La Rosa & P. Soffer (Eds.), BPM 2012 International Workshops (pp. 768–779). Springer. http://hdl.handle.net/20.500.12708/54200
    Project: Brigid (2010–2015)
  • Supporting Shared Decision Making within the MobiGuide Project / Quaglini, S., Shahar, Y., Peleg, M., Miksch, S., Napolitano, C., Rigla, M., Pallàs, A., Parimbelli, E., & Sacchi, L. (2013). Supporting Shared Decision Making within the MobiGuide Project. In Proceedings of the AMIA Annual Symposium (pp. 1175–1184). American Medical Informatics Association (AMIA). http://hdl.handle.net/20.500.12708/54900
    Project: MobiGuide (2011–2015)
  • Process Support and Knowledge Representation in Health Care / Process Support and Knowledge Representation in Health Care. (2013). In R. Lenz, S. Miksch, M. Peleg, M. Reichert, D. Riano, & A. ten Teije (Eds.), Lecture Notes in Computer Science. Springer-Verlag, Lecture Notes in Artificial Intelligence 8268. https://doi.org/10.1007/978-3-642-36438-9
    Project: MobiGuide (2011–2015)
  • Identifying Condition-Action Sentences Using a Heuristic-Based Information Extraction Method / Wenzina, R., & Kaiser, K. (2013). Identifying Condition-Action Sentences Using a Heuristic-Based Information Extraction Method. In D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, & A. ten Teije (Eds.), Lecture Notes in Computer Science (pp. 26–38). Springer Verlag, LNAI 8268. https://doi.org/10.1007/978-3-319-03916-9_3
    Project: Brigid (2010–2015)
  • Supporting Computer-interpretable Guidelines’ Modeling by Automatically Classifying Clinical Actions / Minard, A.-L., & Kaiser, K. (2013). Supporting Computer-interpretable Guidelines’ Modeling by Automatically Classifying Clinical Actions. In D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, & A. ten Teije (Eds.), Lecture Notes in Computer Science (pp. 39–52). Springer Verlag, LNAI 8268. https://doi.org/10.1007/978-3-319-03916-9_4
    Projects: Brigid (2010–2015) / MobiGuide (2011–2015)
  • How Do You Connect Moving Dots? Insights from User Studies on Dynamic Network Visualizations / Smuc, M., Federico, P., Windhager, F., Aigner, W., Zenk, L., & Miksch, S. (2013). How Do You Connect Moving Dots? Insights from User Studies on Dynamic Network Visualizations. In W. Huang (Ed.), Handbook of Human Centric Visualization (pp. 623–650). Springer. https://doi.org/10.1007/978-1-4614-7485-2_25
  • Process Support and Knowledge Representation in Health Care / Process Support and Knowledge Representation in Health Care. (2013). In D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, & A. ten Teije (Eds.), Lecture Notes in Computer Science. Springer-Verlag, Lecture Notes in Artificial Intelligence 8268. https://doi.org/10.1007/978-3-319-03916-9
    Project: MobiGuide (2011–2015)

2012

2011

  • Towards a Concept how the Structure of Time can Support the Visual Analytics Process / Lammarsch, T., Aigner, W., Bertone, A., Miksch, S., & Rind, A. (2011). Towards a Concept how the Structure of Time can Support the Visual Analytics Process. In S. Miksch & G. Santucci (Eds.), Proceedings of the Second International Workshop on Visual Analytics held in Europe (EuroVA 2011) (pp. 9–12). Computer Graphics Forum. https://doi.org/10.2312/PE/EuroVAST/EuroVA11/009-012
    Project: HypoVis (2011–2015)
  • Bertin was Right: An Empirical Evaluation of Indexing to Compare Multivariate Time-Series Data Using Line Plots / Aigner, W., Kainz, C., Ma, R., & Miksch, S. (2011). Bertin was Right: An Empirical Evaluation of Indexing to Compare Multivariate Time-Series Data Using Line Plots. Computer Graphics Forum, 30(1), 215–228. http://hdl.handle.net/20.500.12708/162118
  • Information requisition is the core of guideline-based medical care: which information is needed for whom? / Gschwandtner, T., Kaiser, K., & Miksch, S. (2011). Information requisition is the core of guideline-based medical care: which information is needed for whom? Journal of Evaluation in Clinical Practice, 17, 713–721. http://hdl.handle.net/20.500.12708/161736
  • Visual Enterprise Network Analytics - Visualizing Organizational Change / Windhager, F., Zenk, L., & Federico, P. (2011). Visual Enterprise Network Analytics - Visualizing Organizational Change. Procedia - Social and Behavioral Sciences, 22, 59–68. https://doi.org/10.1016/j.sbspro.2011.07.056
    Project: VIENA (2011–2013)
  • Patient Development at a Glance: An Evaluation of a Medical Data Visualization / Pohl, M., Wiltner, S., Rind, A., Aigner, W., Miksch, S., Turic, T., & Drexler, F. (2011). Patient Development at a Glance: An Evaluation of a Medical Data Visualization. In P. Campos, N. Graham, J. Jorge, N. Nunes, P. Palanque, & M. Winckler (Eds.), Human-Computer Interaction – INTERACT 2011 (pp. 292–299). Springer Berlin / Heidelberg. https://doi.org/10.1007/978-3-642-23768-3_24
  • Visual analytics of dynamic social networks / Federico, P. (2011). Visual analytics of dynamic social networks. IEEE VisWeek 2011 Doctoral Colloquium, Providence, RI, Non-EU. http://hdl.handle.net/20.500.12708/85162
    Project: VIENA (2011–2013)
  • Visual Analytics of Dynamic Networks - A Case Study / Federico, P., Aigner, W., Miksch, S., Windhager, F., & Zenk, L. (2011). Visual Analytics of Dynamic Networks - A Case Study. The Third International UKVAC Workshop on Visual Analytics (VAW 2011), London, UK, EU. http://hdl.handle.net/20.500.12708/85147
    Project: VIENA (2011–2013)
  • Towards a Concept how the Structure of Time can Support the Visual Analytics Process / Lammarsch, T. (2011). Towards a Concept how the Structure of Time can Support the Visual Analytics Process. Seminar at the University of Rostock, Rostock, Germany, EU. http://hdl.handle.net/20.500.12708/85555
  • 2011 IEEE Conference on Visual Analytics Science and Technology (VAST) / Miksch, S., & Ward, M. (Eds.). (2011). 2011 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE Computer Society Press. https://doi.org/10.1109/VAST19326.2011
    Projects: HypoVis (2011–2015) / VIENA (2011–2013)
  • Visually Exploring Multivariate Trends in Patient Cohorts Using Animated Scatter Plots / Rind, A., Aigner, W., Miksch, S., Wiltner, S., Pohl, M., Drexler, F., Neubauer, B., & Suchy, N. (2011). Visually Exploring Multivariate Trends in Patient Cohorts Using Animated Scatter Plots. In M. M. Robertson (Ed.), Ergonomics and Health Aspects of Work with Computers (pp. 139–148). Springer. https://doi.org/10.1007/978-3-642-21716-6_15
  • Supporting Knowledge Modelling by Multi-modal Learning: Defining the Requirements / Kaiser, K., & Seyfang, A. (2011). Supporting Knowledge Modelling by Multi-modal Learning: Defining the Requirements. In D. Riano, A. ten Teije, & S. Miksch (Eds.), Proc. of the Workshop on Knowledge Representation for Healthcare (KR4HC) in conjunction with the Conference on Artificial Intelligence 2011 (p. 11). http://hdl.handle.net/20.500.12708/53797
    Project: Brigid (2010–2015)
  • Visual Exploration of Time-Oriented Patient Data for Chronic Diseases: Design Study and Evaluation / Rind, A., Aigner, W., Miksch, S., Wiltner, S., Pohl, M., Turic, T., & Drexler, F. (2011). Visual Exploration of Time-Oriented Patient Data for Chronic Diseases: Design Study and Evaluation. In A. Holzinger & K.-M. Simonic (Eds.), Lecture Notes in Computer Science (pp. 301–320). Springer. https://doi.org/10.1007/978-3-642-25364-5_22
  • A visual analytics approach to dynamic social networks / Federico, P., Aigner, W., Miksch, S., Windhager, F., & Zenk, L. (2011). A visual analytics approach to dynamic social networks. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies - i-KNOW ’11. International Conference on Knowledge Management and Knowledge Technologies (I-KNOW), Special Track on Theory and Applications of Visual Analytics (TAVA), Graz, Austria. ACM. https://doi.org/10.1145/2024288.2024344
    Project: VIENA (2011–2013)
  • Design and Evaluation of an Interactive Visualization of Therapy Plans and Patient Data / Gschwandtner, T., Aigner, W., Kaiser, K., Miksch, S., & Seyfang, A. (2011). Design and Evaluation of an Interactive Visualization of Therapy Plans and Patient Data. In Proceedings of the 25th BCS Conference on Human-Computer Interaction (HCI 2011) (pp. 421–428). BCS. http://hdl.handle.net/20.500.12708/53666
  • A-plan / Schneider, T., & Aigner, W. (2011). A-plan. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies - i-KNOW ’11. International Conference on Knowledge Management and Knowledge Technologies (I-KNOW), Special Track on Theory and Applications of Visual Analytics (TAVA), Graz, Austria. ACM. https://doi.org/10.1145/2024288.2024341
  • Contingency Wheel: Visual Analysis of Large Contingency Tables / Alsallakh, B., Gröller, E., Miksch, S., & Suntinger, M. (2011). Contingency Wheel: Visual Analysis of Large Contingency Tables. In S. Miksch & G. Santucci (Eds.), Proceedings of International Workshop on Visual Analytics (EuroVA 2011) (pp. 53–56). The Eurographics Association. http://hdl.handle.net/20.500.12708/53658
  • Understanding the Role and Value of Interaction: First Steps / Aigner, W. (2011). Understanding the Role and Value of Interaction: First Steps. In S. Miksch & G. Santucci (Eds.), Proceedings of International Workshop on Visual Analytics (EuroVA 2011) (pp. 17–20). The Eurographics Association. http://hdl.handle.net/20.500.12708/53648
  • CareCruiser: Exploring and visualizing plans, events, and effects interactively / Gschwandtner, T., Aigner, W., Kaiser, K., Miksch, S., & Seyfang, A. (2011). CareCruiser: Exploring and visualizing plans, events, and effects interactively. In G. Di Battista, J.-D. Fekete, & H. Qu (Eds.), 2011 IEEE Pacific Visualization Symposium. IEEE. https://doi.org/10.1109/pacificvis.2011.5742371
  • International Workshop on Visual Analytics (EuroVA 2011) / Miksch, S., & Santucci, G. (Eds.). (2011). International Workshop on Visual Analytics (EuroVA 2011). Eurographics Association. http://hdl.handle.net/20.500.12708/23443
  • Identifying Treatment Activities for Modelling Computer-Interpretable Clinical Practice Guidelines / Kaiser, K., Seyfang, A., & Miksch, S. (2011). Identifying Treatment Activities for Modelling Computer-Interpretable Clinical Practice Guidelines. In D. Riano, A. ten Teije, S. Miksch, & M. Peleg (Eds.), Knowledge Representation for Health-Care (pp. 115–126). Springer Verlag, LNAI 6512. http://hdl.handle.net/20.500.12708/26923
    Projects: Brigid (2010–2015) / REMINE (2008–2013)
  • Visualization of Time-Oriented Data / Aigner, W., Miksch, S., Schumann, H., & Tominski, C. (2011). Visualization of Time-Oriented Data. In Human-Computer Interaction Series. Springer. https://doi.org/10.1007/978-0-85729-079-3

2010

2009

2008

  • Visualization Methods to Support Guideline-Based Care Management / Aigner, W., Kaiser, K., & Miksch, S. (2008). Visualization Methods to Support Guideline-Based Care Management. In A. ten Teije, S. Miksch, & P. Lucas (Eds.), Computer-based Medical Guidelines and Protocols: A Primer and Current Trends (pp. 140–159). IOS Press. https://doi.org/10.3233/978-1-58603-873-1-140
    Project: EviX (2006–2009)
  • Computer-Interpretable Guideline Formalisms / de Clercq, P., Kaiser, K., & Hasman, A. (2008). Computer-Interpretable Guideline Formalisms. In A. ten Teije, S. Miksch, & P. Lucas (Eds.), Computer-based Medical Guidelines and Protocols: A Primer and Current Trends (pp. 22–43). IOS Press. https://doi.org/10.3233/978-1-58603-873-1-22
    Project: EviX (2006–2009)
  • Improving the execution of Clinical Guidelines and Temporal Data Abstraction in High-Frequency Domains / Seyfang, A., Paesold, M., Votruba, P., & Miksch, S. (2008). Improving the execution of Clinical Guidelines and Temporal Data Abstraction in High-Frequency Domains. In A. ten Teije, S. Miksch, & P. Lucas (Eds.), Computer-based Medical Guidelines and Protocols: A Primer and Current Trends (pp. 263–272). IOS Press. https://doi.org/10.3233/978-1-58603-873-1-263
    Project: REMINE (2008–2013)
  • MapFace - An Aid for Medical Experts to Easily Annotate Documents with MetaMap Transfer / Gschwandtner, T., Kaiser, K., Martini, P., & Miksch, S. (2008). MapFace - An Aid for Medical Experts to Easily Annotate Documents with MetaMap Transfer. Workshop on Human-Computer Interaction for Medicine and Health Care (HCI4MED), Liverpool, UK, EU. http://hdl.handle.net/20.500.12708/84745
    Projects: EviX (2006–2009) / REMINE (2008–2013)
  • Visualizations at First Sight: Do Insights Require Training? / Smuc, M., Mayr, E., Lammarsch, T., Bertone, A., Aigner, W., Risku, H., & Miksch, S. (2008). Visualizations at First Sight: Do Insights Require Training? In A. Holzinger (Ed.), Lecture Notes in Computer Science (pp. 261–280). Springer. https://doi.org/10.1007/978-3-540-89350-9_19
  • MapFace - A Graphical Editor to Support the Semantic Annotation of Medical Text / Gschwandtner, T., Kaiser, K., & Miksch, S. (2008). MapFace - A Graphical Editor to Support the Semantic Annotation of Medical Text. In H. Kaiser & R. Kirner (Eds.), Proceedings of the Junior Scientist Conference 2008 (pp. 91–92). http://hdl.handle.net/20.500.12708/52313
  • Easing the Formalization of Clinical Guidelines with a User-tailored, Extensible Agile Model Driven Development (AMDD) / Martini, P., Kaiser, K., & Miksch, S. (2008). Easing the Formalization of Clinical Guidelines with a User-tailored, Extensible Agile Model Driven Development (AMDD). In S. Puuronen, M. Pechenizkiy, A. Tsymbal, & D.-J. Lee (Eds.), Proceedings of the Twenty-First IEEE International Symposium on Computer-Based Medical Systems (pp. 120–125). IEEE Computer Society. http://hdl.handle.net/20.500.12708/52196
    Project: EviX (2006–2009)
  • MapFace - An Editor for MetaMap Transfer (MMTx) / Kaiser, K., Gschwandtner, T., & Martini, P. (2008). MapFace - An Editor for MetaMap Transfer (MMTx). In S. Puuronen, M. Pechenizkiy, A. Tsymbal, & D.-J. Lee (Eds.), Proceedings of the Twenty-First IEEE International Symposium on Computer-Based Medical Systems (pp. 150–152). IEEE Computer Society. http://hdl.handle.net/20.500.12708/52195
    Project: EviX (2006–2009)
  • Syntactical Negation Detection in Clinical Practice Guidelines / Gindl, S., Kaiser, K., & Miksch, S. (2008). Syntactical Negation Detection in Clinical Practice Guidelines. In S. K. Andersen, G. O. Klein, S. Schulz, J. Aarts, & M. C. Mazzoleni (Eds.), eHealth Beyond the Horizon - Get IT There (pp. 187–192). IOS Press. http://hdl.handle.net/20.500.12708/52181
    Project: EviX (2006–2009)
  • Computer-based Medical Guidelines and Protocols: A Primer and Current Trends / ten Teije, A., Miksch, S., & Lucas, P. (Eds.). (2008). Computer-based Medical Guidelines and Protocols: A Primer and Current Trends. IOS Press. http://hdl.handle.net/20.500.12708/22772

2007

2006

2005

2004

  • TimeWrap - A Method for Automatic Transformation of Structured Guideline Components into Formal Process-Representations / Kaiser, K., & Miksch, S. (2004). TimeWrap - A Method for Automatic Transformation of Structured Guideline Components into Formal Process-Representations. In J. Zvárová, P. Hanzlicek, J. Peleska, P. Precková, V. Svátek, & Z. Valenta (Eds.), Proceedings of the International Joint Meeting EuroMISE 2004 (p. 95). EuroMISE. http://hdl.handle.net/20.500.12708/50961
  • CareVis: Integrated Visualization of Computerized Protocols and Temporal Patient Data / Aigner, W., & Miksch, S. (2004). CareVis: Integrated Visualization of Computerized Protocols and Temporal Patient Data. In Workshop Notes of the Workshop on Intelligent Data Analyis in Medicine and Pharmacology (pp. 55–60). http://hdl.handle.net/20.500.12708/50964
  • Protocure: Supporting the Development of Medical Protocols Through Formal Methods / Balser, M., Coltell, O., van Croonenborg, J., Duelli, C., van Harmelen, F., Jovell, A., Lucas, P., Marcos, M., Miksch, S., Reif, W., Rosenbrand, K., Seyfang, A., & ten Teije, A. (2004). Protocure: Supporting the Development of Medical Protocols Through Formal Methods. In J. Zvárová, P. Hanzlicek, J. Peleska, P. Precková, V. Svátek, & Z. Valenta (Eds.), Proceedings of the International Joint Meeting EuroMISE 2004 (p. 81). EuroMISE. http://hdl.handle.net/20.500.12708/50978
  • Protocure: Supporting the Development of Medical Protocols Through Formal Methods / Balser, M., Coltell, O., van Croonenborg, J., Duelli, C., van Harmelen, F., Jovell, A., Lucas, P., Marcos, M., Miksch, S., Reif, W., Rosenbrand, K., Seyfang, A., & ten Teije, A. (2004). Protocure: Supporting the Development of Medical Protocols Through Formal Methods. In K. Kaiser, S. Miksch, & S. W. Tu (Eds.), Computer-based Support for Clinical Guidelines and Protocols (pp. 103–107). http://hdl.handle.net/20.500.12708/50976
  • Advanced Temporal Data Abstraction for Guideline Execution / Seyfang, A., & Miksch, S. (2004). Advanced Temporal Data Abstraction for Guideline Execution. In K. Kaiser, S. Miksch, & S. W. Tu (Eds.), Computer-based Support for Clinical Guidelines and Protocols (pp. 88–102). IOS Press. http://hdl.handle.net/20.500.12708/50969
  • Advanced Temporal Data Abstraction for Guideline Execution / Seyfang, A., & Miksch, S. (2004). Advanced Temporal Data Abstraction for Guideline Execution. In J. Zvárová, P. Hanzlicek, J. Peleska, P. Precková, V. Svátek, & Z. Valenta (Eds.), Proceedings of the International Joint Meeting EuroMISE 2004 (p. 94). EuroMISE. http://hdl.handle.net/20.500.12708/50968
  • Communicating the Logic of a Treatment Plan Formulated in Asbru to Domain Experts / Aigner, W., & Miksch, S. (2004). Communicating the Logic of a Treatment Plan Formulated in Asbru to Domain Experts. In J. Zvárová, P. Hanzlicek, J. Peleska, P. Precková, V. Svátek, & Z. Valenta (Eds.), Proceedings of the International Joint Meeting EuroMISE 2004 (p. 75). EuroMISE. http://hdl.handle.net/20.500.12708/50962
  • Specification of AsbruLight / Seyfang, A., Miksch, S., & Votruba, P. (2004). Specification of AsbruLight. http://hdl.handle.net/20.500.12708/33014
  • MHB - A Many-Headed Bridge between Guideline Formats / Seyfang, A., Miksch, S., Votruba, P., Rosenbrand, K., Wittenberg, J., van Croonenborg, J., Reif, W., Balser, M., Schmitt, J., von der Weide, T., Lucas, P., & Hommersom, A. (2004). MHB - A Many-Headed Bridge between Guideline Formats. http://hdl.handle.net/20.500.12708/33013
  • Treating Temporal Information in Plan and Process Modeling / Kaiser, K., & Miksch, S. (2004). Treating Temporal Information in Plan and Process Modeling. http://hdl.handle.net/20.500.12708/32942

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  • Silvia Miksch: Bridging the Gap between Visual Analytics and Digital Humanities: Beyond the Data-Users-Tasks Design Triangle
    2019 / Best Paper Award at VIS workshop vis4dh (IEEE VIS Conference) / USA / Website
  • Silvia Miksch: The Fabric of Heroes: an Infographic about Marvel Cinematic Universe
    2019 / Third prize winner at International Symposium on Graph Drawing and Network Visualization Creative Topic Challenge, Contest / Czech Republic / Website
  • Silvia Miksch: The Circle Of Thrones: Conveying the Story of Game of Thrones Using Radial Infographics
    2018 / Third prize winner at International Symposium on Graph Drawing and Network Visualization Creative Topic Challenge, Contest / Spain / Website
  • Silvia Miksch: Visually and Statistically Guided Imputation of Missing Values in Univariate Seasonal Time Series
    2015 / Best Poster Award at IEEE Conference on Visual Analytics Science and Technology (VAST) / USA
  • Silvia Miksch: Honorable Mention at IEEE Conference on Visual Analytics Science and Technology (VAST) 2012
    2012 / IEEE Computer Society Visualization & Graphics Technical Committee (VGTC) / USA
  • Wolfgang Aigner: Honorable Mention at IEEE Conference on Visual Analytics Science and Technology (VAST) 2012
    2012 / IEEE Computer Society Visualization & Graphics Technical Committee (VGTC) / USA
  • Silvia Miksch: Recognition of Service Award
    2012 / Eurographics: European Association for Computer Graphics
  • Silvia Miksch: Karl Ritter von Ghega Award of Recognition for the research project "VisuExplore"
    2010 / Karl-Ritter-von-Ghega-Preis / Austria
  • Silvia Miksch: Top Cited Article 2005-2010 in Computers and Graphics
    2010 / Pergamon/Elsevier / Netherlands
  • Wolfgang Aigner: Federal Ministry of Science and Research (BM.WF): Sparkling Science Award for the cooperative research project "HorizonVis" with the school HTBL Krems
    2010 / Austria
  • Wolfgang Aigner: Top Cited Article 2005-2010 in Computers and Graphics
    2010 / Pergamon/Elsevier / Netherlands
  • Wolfgang Aigner: Karl Ritter von Ghega Award of Recognition for the research project "VisuExplore"
    2010 / Karl-Ritter-von-Ghega-Preis / Austria
  • Wolfgang Aigner: Federal Ministry of Science and Re- search (BM.WF): Sparkling Science Award for the cooperative research project "StackFlow 3D" with the school HTBL Krems
    2009 / Austria
  • Silvia Miksch: Karl Ritter von Ghega Award of Recognition for the research project "DisCo"
    2008 / Karl-Ritter-von-Ghega-Preis / Austria
  • Wolfgang Aigner: Karl Ritter von Ghega Award of Recognition for the research project "DisCo"
    2008 / Karl-Ritter-von-Ghega-Preis / Austria
  • Wolfgang Aigner: Award of Special Recognition
    2004 / Austrian Society of Artificial Intelligence(ÖGAI) / Austria
  • Wolfgang Aigner: Outstanding Achievement Award
    2003 / Austria
  • Wolfgang Aigner: Outstanding Achievement Award
    1999 / Johannes Kepler University Linz / Austria

Soon, this page will include additional information such as reference projects, conferences, events, and other research activities.

Until then, please visit Visual Analytics’ research profile in TISS .