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 ( reposiTUm)

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 ( reposiTUm)

Ceneda, D., Arleo, A., Gschwandtner, T., & Miksch, S. (2021). Show Me Your Face: Towards an Automated Method to Provide Timely Guidance in Visual Analytics. IEEE Transactions on Visualization and Computer Graphics, 28(12), 4570–4581. https://doi.org/10.1109/tvcg.2021.3094870 ( reposiTUm)

A. Leite, R., Arleo, A., Sorger, J., Gschwandtner, T., & Miksch, S. (2020). Hermes: Guidance-enriched Visual Analytics for Economic Network Exploration. Visual Informatics, 4(4), 11–22. https://doi.org/10.1016/j.visinf.2020.09.006 ( reposiTUm)

Walch, A., Schwärzler, M., Luksch, C., Eisemann, E., & Gschwandtner, T. (2020). LightGuider: Guiding Interactive Lighting Design using Suggestions, Provenance, and Quality Visualization. IEEE Transactions on Visualization and Computer Graphics, 569–578. https://doi.org/10.1109/tvcg.2019.2934658 ( reposiTUm)

A. Leite, R., Gschwandtner, T., Miksch, S., Gstrein, E., & Kuntner, J. (2020). NEVA: Visual Analytics to Identify Fraudulent Networks. Computer Graphics Forum, 39(6), 344–359. https://doi.org/10.1111/cgf.14042 ( reposiTUm)

Ceneda, D., Andrienko, N., Andrienko, G., Gschwandtner, T., Miksch, S., Piccolotto, N., Schreck, T., Streit, M., Suschnigg, J., & Tominski, C. (2020). Guide Me in Analysis: A Framework for Guidance Designers. Computer Graphics Forum, 39(6), 269–288. https://doi.org/10.1111/cgf.14017 ( reposiTUm)

Bors, C., Gschwandtner, T., & Miksch, S. (2019). Capturing and Visualizing Provenance From Data Wrangling. IEEE Computer Graphics and Applications, 39(6), 61–75. https://doi.org/10.1109/mcg.2019.2941856 ( reposiTUm)

Ceneda, D., Gschwandtner, T., & Miksch, S. (2019). You get by with a little help: The effects of variable guidance degrees on performance and mental state. Visual Informatics, 3(4), 177–191. https://doi.org/10.1016/j.visinf.2019.10.005 ( reposiTUm)

Ceneda, D., Gschwandtner, T., & Miksch, S. (2019). A review of guidance approaches in visual data analysis: A multifocal perspective. Computer Graphics Forum, 38(3), 861–879. https://doi.org/10.1111/cgf.13730 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

Bors, C., Kriglstein, S., Gschwandtner, T., Miksch, S., & Pohl, M. (2018). Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics. ACM Journal of Data and Information Quality, 10(1), 1–26. https://doi.org/10.1145/3190578 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

Gschwandtner, T., Kaiser, K., Martini, P., & Miksch, S. (2010). Easing Semantically Enriched Information Retrieval - An Interactive Semi-Automatic Annotation System for Medical Documents. International Journal of Human-Computer Studies, 68(6), 370–385. https://doi.org/10.1016/j.ijhcs.2009.08.002 ( reposiTUm)

Bors, C., Bernard, J., Bögl, M., Gschwandtner, T., Kohlhammer, J., & Miksch, S. (2019). Quantifying Uncertainty in Multivariate Time Series Pre-Processing. In T. von Landesberger & C. Turkay (Eds.), EuroVis Workshop on Visual Analytics (pp. 31–35). Proceedings of the 21st EG/VGTC Conference on Visualization (EuroVis 2019). https://doi.org/10.2312/eurova.20191121 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

Gschwandtner, T., Kaiser, K., & Miksch, S. (2010). Information Requisition for Computer-Supported Medical Care. In H. Kaiser & R. Kirner (Eds.), Proceedings of the Junior Scientist Conference 2010 (pp. 65–66). http://hdl.handle.net/20.500.12708/53135 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

Freund, R., & Gschwandtner, T. (2006). P Systems for Modelling Biological Processes in Living Cells. In R. Freund & M. Oswald (Eds.), Proceedings 16.Theorietag Automaten und Formale Sprachen (pp. 46–50). http://hdl.handle.net/20.500.12708/51737 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

Ceneda, D., Gschwandtner, T., & Miksch, S. (2019). A Review of Guidance Approaches in Visual Data Analysis:A Multifocal Perspective. 21st EG/VGTC Conference on Visualization (EuroVis 2019), Porto, Portugal, EU. http://hdl.handle.net/20.500.12708/86875 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

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 ( reposiTUm)

Gschwandtner, T. (2012). CareCruiser - Interactive Exploration of Effects of Therapeutic Actions on a Patient’s Condition. EuroVis 2012 LabVisit, Wien, Austria. http://hdl.handle.net/20.500.12708/85352 ( reposiTUm)

Gschwandtner, T. (2009). Interactive Visualization to Optimize Treatment Choices for Individual Patients. IEEE VisWeek 2009 Doctoral Colloquium, Atlantic City, NJ, USA, Non-EU. http://hdl.handle.net/20.500.12708/84943 ( reposiTUm)

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 ( reposiTUm)

Gschwandtner, T., Kaiser, K., Miksch, S., & Seyfang, A. (2010). ReMINE Deliverable 4.8 -- Third Release of the Adverse Risk Management Support System (4.8). http://hdl.handle.net/20.500.12708/36650 ( reposiTUm)

Gschwandtner, T., Kaiser, K., & Seyfang, A. (2009). ReMINE Deliverable 4.7 -- First Release of the Adverse Risk Management Support System (D 4.7). http://hdl.handle.net/20.500.12708/35990 ( reposiTUm)

Gschwandtner, T., Kaiser, K., Miksch, S., & Seyfang, A. (2009). ReMINE Internal Deliverable -- Second Release of the Adverse Risk Management Support System. http://hdl.handle.net/20.500.12708/35994 ( reposiTUm)

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 ( reposiTUm)

Gschwandtner, T. (2012). Interactive visualization of effects of medical treatment on a patients condition [Dissertation, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-55140 ( reposiTUm)

Gschwandtner, T. (2009). Information requisition is the core of guideline-based medical care : which information is needed for whom? [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-34469 ( reposiTUm)

Gschwandtner, T. (2008). MapFace - a graphical editor for MetaMap Transfer (MMTx) [Master Thesis, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-26131 ( reposiTUm)