SEVA

Zurück

FH-Prof. Priv.-Doz. Dipl.-Ing. Dr. Wolfgang Aigner MSc

  • Stellvertretender Leiter Fakultät für Technik und Wirtschaft
Arbeitsplatz: B - Campus-Platz 1
M: +43/676/847 228 611

Studiengänge

  • Medientechnik (BA)
  • Digital Innovation and Research (MA)
  • Interactive Technologies (MA)
  • Digital Media Production (MA)
  • Creative Computing (BA)
  • Data Science and Artificial Intelligence (BA)
  • Digital Design (MA)
  • Data Intelligence (MA)
  • Digitale Medientechnologien (MA)

Departments

  • Medien und Digitale Technologien
  • Informatik und Security
Wolfgang Aigner ist Experte für Informationsvisualisierung (InfoVis) und Visual Analytics (VA) mit einem Fokus auf zeitorientierte Daten. In seiner Forschung und Lehre beschäftigt er sich mit Computerwerkzeugen, Methoden und Konzepten, die Menschen im Umgang mit großen und komplexen Informationsstrukturen unterstützen um komplexe Sachverhalte verständlich zu machen, die Gewinnung neuer Erkenntnisse zu erleichtern und die Generierung neuen Wissens zu ermöglichen. Wolfgang Aigner hat an mehr als 125 Publikationen mitgewirkt und ist ein Autor des Buchs “Visualization of Time-Oriented Data” (Springer, 2011).
Vollständige Publikationsliste

Projekte

Ausgewählte Publikationen

Bibtex für alle Ergebnisse downloaden
Stoiber, C., Rind, A., Grassinger, F., Gutounig, R., Goldgruber, E., Sedlmair, M., Emrich, S., & Aigner, W. (2019). netflower: Dynamic Network Visualization for Data Journalists. Computer Graphics Forum (EuroVis "19), 38. https://doi.org/10/ghm4jz
Wagner, M., Slijepcevic, D., Horsak, B., Rind, A., Zeppelzauer, M., & Aigner, W. (2018). KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis. IEEE Transactions on Visualization and Computer Graphics (TVCG), 25(3), 1528–1542. https://doi.org/10/ghppzn
Niederer, C., Stitz, H., Hourieh, R., Grassinger, F., Aigner, W., & Streit, M. (2018). TACO: Visualizing Changes in Tables Over Time. IEEE Transactions on Visualization and Computer Graphics (InfoVis "17), 24(1), 677–686. https://doi.org/10/ghppzq
Wagner, M., Rind, A., Thür, N., & Aigner, W. (2017). A knowledge-assisted visual malware analysis system: design, validation, and reflection of KAMAS. Computers & Security, 67, 1–15. https://doi.org/10/b5j9
Federico, P., Wagner, M., Rind, A., Amor-Amorós, A., Miksch, S., & Aigner, W. (2017). The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics. IEEE Conference on Visual Analytics Science and Technology (VAST), 92–103. https://doi.org/10/ghppzr
Tominski, C., Aigner, W., Miksch, S., & Schumann, H. (2017). Images of Time: Visual Representation of Time-Oriented Data. In A. Black, P. Luna, O. Lund, & S. Walker (Eds.), Information Design: Research and Practice (pp. 23–42). Gower/Routledge. http://mc.fhstp.ac.at/sites/default/files/publications/Tominski17ImagesOfTime.pdf
Blumenstein, K., Niederer, C., Wagner, M., Schmiedl, G., Rind, A., & Aigner, W. (2016). Evaluating Information Visualization on Mobile Devices: Gaps and Challenges in the Empirical Evaluation Design Space. Proceedings of 2016 Workshop on Beyond Time And Errors: Novel Evaluation Methods For Visualization, 125–132. https://doi.org/10/cwc6
Rind, A., Aigner, W., Wagner, M., Miksch, S., & Lammarsch, T. (2016). 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/f3szvq
Stitz, H., Gratzl, S., Aigner, W., & Streit, M. (2015). ThermalPlot: Visualizing Multi-Attribute Time-Series Data Using a Thermal Metaphor. IEEE Transactions on Visualization and Computer Graphics, 22, 2594–2607. https://doi.org/10/ghppzs
Wagner, M., Fischer, F., Luh, R., Haberson, A., Rind, A., Keim, D. A., & Aigner, W. (2015). A Survey of Visualization Systems for Malware Analysis. In R. Borgo, F. Ganovelli, & I. Viola (Eds.), Eurographics Conference on Visualization (EuroVis) - STARs (pp. 105–125). The Eurographics Association. https://doi.org/10/cwc4
Alsallakh, B., Micallef, L., Aigner, W., Hauser, H., Miksch, S., & Rodgers, P. (2015). The State-of-the-Art of Set Visualization. Computer Graphics Forum, Early view. https://doi.org/10/cwc5
Aigner, W., Miksch, S., Schumann, H., & Tominski, C. (2015). Visualization Techniques for Time-Oriented Data. In M. O. Ward, G. Grinstein, & D. Keim (Eds.), Interactive Data Visualization: Foundations, Techniques, and Applications (2nd ed., pp. 253–284). A K Peters/CRC Press. https://www.crcpress.com/product/isbn/9781482257373
Miksch, S., & Aigner, W. (2014). A Matter of Time: Applying a Data-Users-Tasks Design Triangle to Visual Analytics of Time-Oriented Data. Computers & Graphics, 38, 286–290. https://doi.org/10/f3szvk
Aigner, W., Hoffmann, S., & Rind, A. (2013). EvalBench: A Software Library for Visualization Evaluation. Computer Graphics Forum, 32(3), 41–50. https://doi.org/10/f3szvb
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/f3szvg
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 (Proceedings of InfoVis), 19, 2496–2505. https://doi.org/10/3v3
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/f3szvd
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 (Proceedings of IEEE VAST 2012), 18(12), 2849–2858. https://doi.org/10/f4fwmj
Aigner, W., Rind, A., & Hoffmann, S. (2012). Comparative Evaluation of an Interactive Time-Series Visualization that Combines Quantitative Data with Qualitative Abstractions. Computer Graphics Forum, 31(3), 995–1004. https://doi.org/10/f9skn4
Aigner, W., Miksch, S., Schumann, H., & Tominski, C. (2011). Visualization of Time-Oriented Data. Springer Verlag; http://www.timeviz.net. https://doi.org/10.1007/978-0-85729-079-3
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. https://doi.org/10/fjf52x
Schneider, T., & Aigner, W. (2011). A-Plan: Integrating Interactive Visualization With Automated Planning for Cooperative Resource Scheduling. Proceedings of International Conference on Knowledge Management and Knowledge Technologies (I-KNOW), Special Track on Theory and Applications of Visual Analytics (TAVA), 44:1-44:8. https://doi.org/10/dzvszp
Smuc, M., Mayr, E., Lammarsch, T., Aigner, W., Miksch, S., & Gärtner, J. (2009). To Score or Not to Score? Tripling Insights for Participatory Design. IEEE Computer Graphics and Applications, 29(3), 29–38. https://doi.org/10/cb6vw8
Aigner, W., Miksch, S., Müller, W., Schumann, H., & Tominski, C. (2008). Visual Methods for Analyzing Time-Oriented Data. IEEE Transactions on Visualization and Computer Graphics, 14(1), 47–60. https://doi.org/10/c2qm3s
Aigner, W., Kaiser, K., & Miksch, S. (2008). Visualization Techniques to Support Authoring, Execution, and Maintenance of Clinical Guidelines. In A. ten Teije, P. Lucas, & S. Miksch (Eds.), Computer-Based Medical Guidelines and Protocols: A Primer and Current Trends (pp. 140–159). IOS Press, Health Technology and Informatics. http://mc.fhstp.ac.at/sites/default/files/publications/2008/aigner_2008_VisuCGP.pdf
Aigner, W., Miksch, S., Müller, W., Schumann, H., & Tominski, C. (2007). Visualizing Time-Oriented Data - A Systematic View. Computers & Graphics, 31(3), 401–409. https://doi.org/10/dxs9t9
Aigner, W., & Miksch, S. (2006). CareVis: Integrated Visualization of Computerized Protocols and Temporal Patient Data. Artifical Intelligence in Medicine (AIIM), 37(3), 203–218. https://doi.org/10/cbwjct

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