TU Wien Informatics

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Silvia Miksch

Univ.Prof.in Mag.a rer.soc.oec. Dr.in rer.soc.oec.

Research Focus

  • Information Systems Engineering: 20%
  • Logic and Computation: 20%
  • Visual Computing and Human-Centered Technology: 60%

Research Areas

  • Visual Computing, Time-oriented Data, Information and Knowledge Engineering, Information Visualization, Information Design, Process Engineering, Plan Management, Medical Informatics, Visual Analytics
Silvia Miksch

About

Visualization (Information Visualization, Visual Analytics), Interaction Design, Process Engineering, time-oriented data

Roles

  • Head of Research Unit
    Visual Analytics, E193-07
  • Full Professor
    Visual Analytics, E193-07
  • Research Focus Coordinator
    Visual Computing and Human-Centered Technology
  • Faculty Council
    Principal Member

Contact

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)
  • The Combinatorics of HumaneAI / Schetinger, V., Eiter, T., Kiesel, R. P. D., & Miksch, S. (2022, November 16). The Combinatorics of HumaneAI [Poster Presentation]. Conference on AI for Humanity and Society, Stockholm, Sweden.
    Project: HumanE-AI-Net (2020–2023)
  • 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).
  • 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)
  • A Typology of Guidance Tasks in Mixed‐Initiative Visual Analytics Environments / Perez Messina, I. B., Ceneda, D., El-Assady, M., Miksch, S., & Sperrle, F. (2022). A Typology of Guidance Tasks in Mixed‐Initiative Visual Analytics Environments. Computer Graphics Forum, 41(3), 465–476. https://doi.org/10.1111/cgf.14555
    Download: PDF (1.02 MB)
    Projects: DoRIAH (2020–2024) / GuidedVA (2020–2024) / KnoVA (2018–2022)
  • A Typology of Guidance in Mixed-Initiative Visual Analytics Environments / Perez Messina, I. B., Ceneda, D., & Miksch, S. (2022, June 16). A Typology of Guidance in Mixed-Initiative Visual Analytics Environments [Conference Presentation]. EuroVis 2022, Rom, Italy. http://hdl.handle.net/20.500.12708/148085
    Download: Presentation (8.53 MB)
    Projects: DoRIAH (2020–2024) / KnoVA (2018–2022)
  • 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
  • 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)
  • 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)
  • 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

2017

  • 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
  • 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 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)
  • 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

  • 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
  • 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)
  • 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

  • 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)
  • 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
  • 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)
  • 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)
  • 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)
  • 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)
  • 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

  • 399 Automatic Control of the Inspired Oxygen Fraction in Preterm Infants. Preliminary Results of a Multicenter Randomized Cross-Over Trial / Hallenberger, A., Urschitz, M., Müller-Hansen, I., Miksch, S., Seyfang, A., Horn, W., & Poets, C. F. (2012). 399 Automatic Control of the Inspired Oxygen Fraction in Preterm Infants. Preliminary Results of a Multicenter Randomized Cross-Over Trial. Archives of Disease in Childhood, 97(Suppl 2), A117–A117. https://doi.org/10.1136/archdischild-2012-302724.0399
  • Semi-automatic drawing of metabolic networks / Droste, P., Wiechert, W., & Nöh, K. (2012). Semi-automatic drawing of metabolic networks. Information Visualization, 11(3), 171–187. https://doi.org/10.1177/1473871611413565
  • Developing an Extended Task Framework for Exploratory Data Analysis Along the Structure of Time / Lammarsch, T., Rind, A., Aigner, W., & Miksch, S. (2012). Developing an Extended Task Framework for Exploratory Data Analysis Along the Structure of Time. In K. Matkovic & G. Santucci (Eds.), Proceedings of the EuroVis Workshop on Visual Analytics in Vienna, Austria (EuroVA 2012) (pp. 31–35). Eurographics Publications. https://doi.org/10.2312/PE/EuroVAST/EuroVA12/031-035
    Project: HypoVis (2011–2015)
  • Reinventing the Contingency Wheel: Scalable Visual Analytics of Large Categorical Data / Alsallakh, B., Aigner, W., Miksch, S., & Gröller, E. (2012). Reinventing the Contingency Wheel: Scalable Visual Analytics of Large Categorical Data. IEEE Transactions on Visualization and Computer Graphics, 18(12), 2849–2858. https://doi.org/10.1109/tvcg.2012.254
  • Static and Dynamic Visual Mappings to Explore Bivariate Data Across Time / Rind, A., Neubauer, B., Aigner, W., & Miksch, S. (2012). Static and Dynamic Visual Mappings to Explore Bivariate Data Across Time. In K. Matkovic & G. Santucci (Eds.), EuroVA 2012 Poster Proceedings (p. 3). http://hdl.handle.net/20.500.12708/54121
    Project: HypoVis (2011–2015)
  • Preface : Europgraphics Conference on Visualization (EuroVis 2012) / Bruckner, S., Miksch, S., & Pfister, H. (2012). Preface : Europgraphics Conference on Visualization (EuroVis 2012). Computer Graphics Forum, 31(3). http://hdl.handle.net/20.500.12708/164900
  • Analysing Interactivity in Information Visualisation / Pohl, M., Wiltner, S., Miksch, S., Aigner, W., & Rind, A. (2012). Analysing Interactivity in Information Visualisation. KI - Künstliche Intelligenz, 26(2), 151–159. https://doi.org/10.1007/s13218-012-0167-6
  • Guest Editors' Introduction: Special Section on the IEEE Conference on Visual Analytics Science and Technology (VAST) / MacEachren, A. M., & Miksch, S. (2012). Guest Editors’ Introduction: Special Section on the IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE Transactions on Visualization and Computer Graphics, 18(5), 660–661. https://doi.org/10.1109/tvcg.2012.85
  • Knowledge Representation for Health-Care / Riano, D., ten Teije, A., & Miksch, S. (Eds.). (2012). Knowledge Representation for Health-Care. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-27697-2
    Project: MobiGuide (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. (2012). Bertin was Right: An Empirical Evaluation of Indexing to Compare Multivariate Time-Series Data Using Line Plots. EuroVis 2012, Wien, Austria. http://hdl.handle.net/20.500.12708/85349
  • Challenges of Time-oriented Data in Visual Analytics for Healthcare / Aigner, W., Federico, P., Gschwandtner, T., Miksch, S., & Rind, A. (2012). Challenges of Time-oriented Data in Visual Analytics for Healthcare. In J. J. Caban & D. Gotz (Eds.), Proceedings of the IEEE VisWeek Workshop on Visual Analytics in Healthcare (p. 4). http://hdl.handle.net/20.500.12708/54241
    Project: MobiGuide (2011–2015)
  • A Taxonomy of Dirty Time-Oriented Data / Gschwandtner, T., Gärtner, J., Aigner, W., & Miksch, S. (2012). A Taxonomy of Dirty Time-Oriented Data. In Lecture Notes in Computer Science (pp. 58–72). Lecture Notes in Computer Science (LNCS) / Springer Berlin / Heidelberg. https://doi.org/10.1007/978-3-642-32498-7_5
  • ViENA: Visual Enterprise Network Analytics / Federico, P., Aigner, W., Miksch, S., Pfeffer, J., Smuc, M., Windhager, F., & Zenk, L. (2012). ViENA: Visual Enterprise Network Analytics. In Poster Proceedings of the 3rd International Eurovis workshop on Visual Analytics (EuroVA) (p. 12). http://hdl.handle.net/20.500.12708/54133
    Project: VIENA (2011–2013)
  • Visual Analysis of Dynamic Networks Using Change Centrality / Federico, P., Pfeffer, J., Aigner, W., Miksch, S., & Zenk, L. (2012). Visual Analysis of Dynamic Networks Using Change Centrality. In 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. The IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Istanbul, Turkey, Non-EU. IEEE. https://doi.org/10.1109/asonam.2012.39
    Project: VIENA (2011–2013)
  • Visual Tracing for the Eclipse Java Debugger / Alsallakh, B., Bodesinsky, P., Gruber, A., & Miksch, S. (2012). Visual Tracing for the Eclipse Java Debugger. In T. Mens, A. Cleve, & R. Ferenc (Eds.), 16th European Conference on Software Maintenance and Reengineering (pp. 545–548). IEEE Computer Society. http://hdl.handle.net/20.500.12708/54119
  • Visualizing Arrays in the Eclipse Java IDE / Alsallakh, B., Bodesinsky, P., Miksch, S., & Nasseri, D. (2012). Visualizing Arrays in the Eclipse Java IDE. In T. Mens, A. Cleve, & R. Ferenc (Eds.), 16th European Conference on Software Maintenance and Reengineering (pp. 541–544). IEEE Computer Society. http://hdl.handle.net/20.500.12708/54118
  • Vertigo zoom / Federico, P., Aigner, W., Miksch, S., Windhager, F., & Smuc, M. (2012). Vertigo zoom. In Proceedings of the International Working Conference on Advanced Visual Interfaces - AVI ’12. 11th International Working Conference on Advanced Visual Interfaces (AVI2012), Capri Island, EU. ACM. https://doi.org/10.1145/2254556.2254640
    Project: VIENA (2011–2013)
  • Visual Knowledge Networks Analytics / Windhager, F., Smuc, M., Zenk, L., Federico, P., Pfeffer, J., Aigner, W., & Miksch, S. (2012). Visual Knowledge Networks Analytics. In J. Liebowitz (Ed.), Knowledge Management Handbook (pp. 187–206). CRC Press. https://doi.org/10.1201/b12285-12
    Project: VIENA (2011–2013)

2011

2010

2009

2008

2007

  • Free and Open Source Enabling Technologies for Patient-Centric, Guideline-Based Clinical Decision Support: A Survey / Leong, T. Y., Kaiser, K., & Miksch, S. (2007). Free and Open Source Enabling Technologies for Patient-Centric, Guideline-Based Clinical Decision Support: A Survey. IMIA Yearbook of Medical Informatics, 16(1), 74–86. https://doi.org/10.1055/s-0038-1638529
    Project: EviX (2006–2009)
  • Evaluating an InfoVis Technique Using Insight Reports / Rester, M., Pohl, M., Wiltner, S., Hinum, K., Miksch, S., Popow, C., & Ohmann, S. (2007). Evaluating an InfoVis Technique Using Insight Reports. In 2007 11th International Conference Information Visualization (IV ’07). Information Visualization, 11th International Conference Information Visualization, IV2007, Zürich, Switzerland, Non-EU. IEEE Computer Society. https://doi.org/10.1109/iv.2007.44
    Project: IN2VIS (mit 188) (2004–2007)
  • Mixing Evaluation Methods for Assessing the Utility of an Interactive InfoVis Technique / Rester, M., Pohl, M., Wiltner, S., Hinum, K., Miksch, S., Popow, C., & Ohmann, S. (2007). Mixing Evaluation Methods for Assessing the Utility of an Interactive InfoVis Technique. In J. A. Jacko (Ed.), Human-Computer Interaction -- Proc. 12th Intl. HCI Conf. (HCII) (pp. 604–613). Springer. http://hdl.handle.net/20.500.12708/51789
    Project: IN2VIS (mit 188) (2004–2007)
  • How can Information Extraction ease formalizing treatment processes in clinical practice guidelines? A method and its evaluation / Kaiser, K., Akkaya, C., & Miksch, S. (2007). How can Information Extraction ease formalizing treatment processes in clinical practice guidelines? A method and its evaluation. Artificial Intelligence in Medicine, 39(2), 151–163. http://hdl.handle.net/20.500.12708/169624
    Project: EviX (2006–2009)
  • A Meta Schema for Evidence Information in Clinical Practice Guidelines as a Basis for Decision-Making / Kaiser, K., Miksch, S., Martini, P., & Öztürk, A. (2007). A Meta Schema for Evidence Information in Clinical Practice Guidelines as a Basis for Decision-Making. In K. A. Kuhn, J. R. Warren, & T. Y. Leong (Eds.), 12th World Congress on Health (Medical) Informatics (Medinfo’2007) (pp. 925–929). IOS Press. http://hdl.handle.net/20.500.12708/51793
    Project: EviX (2006–2009)
  • Embedding the Evidence Information in Guideline Representation Languages / Öztürk, A., Kaiser, K., Martini, P., & Miksch, S. (2007). Embedding the Evidence Information in Guideline Representation Languages. In P. Kokol, V. Podgorelec, D. Micetic-Turk, M. Zorman, & M. Verlic (Eds.), Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS’07) (pp. 512–517). IEEE Computer Society. https://doi.org/10.1109/CBMS.2007.44
    Project: EviX (2006–2009)
  • Maintaining Formal Models of Living Guidelines Efficiently / Seyfang, A., Martinez-Salvador, B., Serban, R., Wittenberg, J., Miksch, S., Marcos, M., ten Teije, A., & Rosenbrand, K. (2007). Maintaining Formal Models of Living Guidelines Efficiently. In R. Bellazzi, A. Abu-Hanna, & J. Hunter (Eds.), Artificial Intelligence in Medicine (pp. 441–446). Springer. http://hdl.handle.net/20.500.12708/176631
  • ontoX - A Method for Ontology-Driven Information Extraction / Yildiz, B., & Miksch, S. (2007). ontoX - A Method for Ontology-Driven Information Extraction. In O. Gervasi & M. L. Gavrilova (Eds.), Computational Science and Its Applications - ICCSA 2007 (pp. 660–673). Springer-Verlag, LNCS 4707. http://hdl.handle.net/20.500.12708/51898
  • Analyzing Populations with Visual and Analytical Methods to Identify Family Clustered Diseases / Fuchsberger, C., Miksch, S., Forer, L., & Pattaro, C. (2007). Analyzing Populations with Visual and Analytical Methods to Identify Family Clustered Diseases. In K. A. Kuhn, T. Y. Leong, & J. R. Warren (Eds.), 12th World Congress on Health (Medical) Informatics (Medinfo’2007) (p. 2). IOS Press. http://hdl.handle.net/20.500.12708/51859
  • Formalizing 'Living Guidelines' using LASSIE: A Multi-step Information Extraction Method / Kaiser, K., & Miksch, S. (2007). Formalizing “Living Guidelines” using LASSIE: A Multi-step Information Extraction Method. In R. Bellazzi, A. Abu-Hanna, & J. Hunter (Eds.), Artificial Intelligence in Medicine. Proceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME 2007) (pp. 401–410). Springer Verlag. http://hdl.handle.net/20.500.12708/51810
    Project: EviX (2006–2009)
  • Ontology-Driven Information Systems: Challenges and Requirements / Yildiz, B., & Miksch, S. (2007). Ontology-Driven Information Systems: Challenges and Requirements. In Proceedings of the International Conference on Semantic Web and Digital Libraries (ICSD-2007) (p. 11). http://hdl.handle.net/20.500.12708/51795
    Project: EviX (2006–2009)
  • Motivating Ontology-Driven Information Extraction / Yildiz, B., & Miksch, S. (2007). Motivating Ontology-Driven Information Extraction. In Proceedings of the International Conference on Semantic Web and Digital Libraries (ICSD-2007) (p. 11). http://hdl.handle.net/20.500.12708/51794
    Project: EviX (2006–2009)
  • Modeling Treatment Processes Using Information Extraction / Kaiser, K., & Miksch, S. (2007). Modeling Treatment Processes Using Information Extraction. In H. Yoshida, A. Jain, A. Ichalkaranje, L. Jain, & N. Ichalkaranje (Eds.), Advanced Computational Intelligence Paradigms in Healthcare 1 (pp. 189–224). Springer-Verlag. http://hdl.handle.net/20.500.12708/25379
    Project: EviX (2006–2009)

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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  • 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
  • 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
  • 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
  • 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
  • Recognition of Service Award
    2012 / Eurographics: European Association for Computer Graphics
  • Honorable Mention at IEEE Conference on Visual Analytics Science and Technology (VAST) 2012
    2012 / IEEE Computer Society Visualization & Graphics Technical Committee (VGTC) / USA
  • Karl Ritter von Ghega Award of Recognition for the research project "VisuExplore"
    2010 / Karl-Ritter-von-Ghega-Preis / Austria
  • Top Cited Article 2005-2010 in Computers and Graphics
    2010 / Pergamon/Elsevier / Netherlands
  • Karl Ritter von Ghega Award of Recognition for the research project "DisCo"
    2008 / Karl-Ritter-von-Ghega-Preis / Austria

Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.

Until then, please visit Silvia Miksch’s research profile in TISS .