CVAST - Centre for Visual Analytics Science and Technology

Submitted by bilal on Thu, 01/03/2013 - 13:58
Aim

CVAST aims to design and  develop innovative methods for data interpretation to capture the daily flood of information in interactive visualizations and analyses. Scenarios that involve temporal properties of such data are in the focus of our scientific interest.

 

alternative webpage @ w-fFORTE

Publications

 

Duration

April 2010 - March 2018

Funding

This project is funded by the Austrian Federal Ministry of Science, Research, and Economy (formerly known as Austrian Federal Ministry of Economy, Family and Youth) in the exceptional Laura Bassi Centres of Excellence initiative, project number: 822746 (Phase 1) /840262 (Phase 2).

Centres of Expertise - Laura Bassi

Contact
Status
finished

CVAST aims to design and  develop innovative methods for data interpretation to capture the daily flood of information in interactive visualizations and analyses. Scenarios that involve temporal properties of such data are in the focus of our scientific interest.

Due to the proliferating capabilities to generate and collect vast amounts of data and information we face the challenge that users and analysts get lost in irrelevant, or otherwise inappropriately processed or presented information. This phenomenon, commonly known as information deluge, overwhelms traditional methods of data analysis such as spreadsheets, ad-hoc queries, or simple visualizations. At the same time, intelligent usage of increasingly available data offers great opportunities to promote technological progress and business success. On this score, Visual Analytics is an emerging research discipline developing methods and technology that make the best possible use of huge information loads in a wide variety of applications. The basic idea is to appropriately combine the strengths of both, computers' and humans' information processing capabilities. To make complex information structures more comprehensible, facilitate new insights, and enable knowledge discovery, methods of visualization, intelligent data analysis, and mining form a symbiosis with the human user via interactive visual interfaces.

The goals of the Centre of Visual Analytics Science and Technology (CVAST) are twofold. The first goal is the integration of the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment. The second goal is to scientifically assess the usability and utility of such discovery environments while bridging the gap between theory and practice for selected application scenarios.

Application scenarios that involve temporal properties are in the focus of our scientific interest. Time - in contrast to other quantitative data dimensions that are usually "flat" - has an inherent structure and distinct characteristics (calendar aspect, natural and social aspects, etc.) which increase its complexity dramatically and demand specialized Visual Analytics methods in order to support proper analysis and visualization. Our expected results will be Innovative, user-oriented, and task-specific Visual Analytics methods and tools with an assessment of their usability and utility. These methods will be used intertwinedly and iteratively to ease the explorative information discovery processes

An appropriate framework for these methods and tools. Their evaluation in 'real life' environments and examination of the information discovery process within several application scenarios. A new methodology to define and evaluate insights facilitated by these methods. Applying these methods within commercial applications to illustrate their business value and economic impacts

Publications

2018
Theresia Gschwandtner, Oliver Erhart, "Know Your Enemy: Identifying Quality Problems of Time Series Data", IEEE Pacific Visualization Symposium (PacificVis '18), pp. 205-214, 2018. paper
Christian Bors, Theresia Gschwandtner, Simone Kriglstein, Silvia Miksch, Margit Pohl, "Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics", Journal of Data and Information Quality (JDIQ), vol. 10, pp. 3:1–3:26, 2018. paper
Roger Leite, Theresia Gschwandtner, Silvia Miksch, Simone Kriglstein, Margit Pohl, Erich Gstrein, Johannes Kuntner, "EVA: Visual Analytics to Identify Fraudulent Events", IEEE Transactions on Visualization and Computer Graphics, vol. 24, pp. 330 - 339, 2018. paper video
Davide Ceneda, Theresia Gschwandtner, Thorsten May, Silvia Miksch, Marc Streit, Christian Tominski, "Guidance or No Guidance? A Decision Tree Can Help", EuroVA: International Workshop on Visual Analytics, pp. 19–23, 2018. paper
Velitchko Filipov, Paolo Federico, Silvia Miksch, "CV3: Visual Exploration, Assessment, and Comparison of CVs", EuroVis 2018 - Posters, 2018.
Natalia Andrienko, Tim Lammarsch, Gennady Andrienko, Georg Fuchs, Daniel Keim, Silvia Miksch, Alexander Rind, "Viewing Visual Analytics as Model Building", Computer Graphics Forum, vol. 37, pp. 275–299, 2018. paper
Christian Bors, Simone Kriglstein, Theresia Gschwandtner, Silvia Miksch, Margit Pohl, "Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics", Journal of Data and Information Quality (JDIQ), vol. Forthcoming, 2018.
Andreas Peterschofsky, Theresia Gschwandtner, "VoD - Understanding Structure, Content, and Quality of a Dataset", IEEE VIS Workshop on Visual Summarization and Report Generation: Beyond Scatter-Plots and Bar-Charts (VISREG 2018), 2018. paper
Alice Thud, Theresia Gschwandtner, Jagoda Walny, Jason Dykes, John Stasko, "Exploration and Explanation in Data-Driven Storytelling", Data-Driven Storytelling, 2018. paper
Fabian Schwarzinger, Andreas Roschal, Theresia Gschwandtner, "Sketching Temporal Uncertainty - An Exploratory User Study", EuroVis 2018 - Short Papers, Eurographics/IEEE VGTC Conference on Visualization, pp. 67-71, 2018. paper supplemental material
2017
Christian Bors, Markus Bögl, Theresia Gschwandtner, Silvia Miksch, "Visual Support for Rastering of Unequally Spaced Time Series", 10th International Symposium on Visual Information Communication and Interaction (VINCI), pp. 53-57, 2017. paper
Christian Bors, Markus Bögl, Theresia Gschwandtner, Silvia Miksch, "Visual Support for Rastering of Unequally Spaced Time Series", Data Science, Statistics & Visualisation Conference (DSSV), 2017. paper
Davide Ceneda, Theresia Gschwandtner, Thorsten May, Silvia Miksch, Hans-Jörg Schulz, Marc Streit, Christian Tominski, "Characterizing Guidance in Visual Analytics", IEEE Transactions on Visualization and Computer Graphics, vol. 23, pp. 111-120, 2017. paper
Theresia Gschwandtner, "Visual Analytics Meets Process Mining: Challenges and Opportunities", Fifth International Symposium on Data-Driven Process Discovery and Analysis, vol. 244, 2017. paper
Davide Ceneda, Theresia Gschwandtner, Thorsten May, Silvia Miksch, Hans-Jörg Schulz, Marc Streit, Christian Tominski, "Amending the Characterization of Guidance in Visual Analytics", ArXiv, vol. Human-computer Interaction, 2017. paper
Alexander Rind, Paolo Federico, Theresia Gschwandtner, Wolfgang Aigner, Jakob Doppler, Markus Wagner, "Visual Analytics of Electronic Health Records with a Focus on Time", New Perspectives in Medical Records: Meeting the Needs of Patients and Practitioners, pp. 65-77, 2017.
Paolo Federico, "Visual Analytics of Dynamic Networks", Faculty of Informatics, vol. PhD in Computer Science, pp. 192, 2017. paper
Markus Bögl, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Roger Leite, Silvia Miksch, Alexander Rind, "Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction", Computer Graphics Forum, vol. 36, pp. 227–238, 2017. paper Usage Scenario
Albert Amor-Amorós, Paolo Federico, Silvia Miksch, Sebastian Zambanini, Simon Brenner, Robert Sablatnig, "Visual Analytics for Multitemporal Aerial Image Georeferencing", 8th International EuroVis Workshop on Visual Analytics (EuroVA), pp. 55–59, 2017. paper
2016
Hendrik Strobelt, Bilal Alsallakh, Joseph Botros, Peterson Brant, Mark Borowsky, Hanspeter Pfister, Alexander Lex, "Vials: Visualizing Alternative Splicing of Genes", IEEE Transactions of Visualization and Computer Graphics , vol. 22, pp. 399-408, 2016. paper Problem description
Jürgen Bernard, Eduard Dobermann, Markus Bögl, Martin Röhlig, Anna Vögele, Jörn Kohlhammer, "Visual-Interactive Segmentation of Multivariate Time Series", EuroVis Workshop on Visual Analytics (EuroVA), 2016. paper
Davide Ceneda, Wolfgang Aigner, Markus Bögl, Theresia Gschwandtner, Silvia Miksch, "Guiding the Visualization of Time-oriented Data", Proceedings of the IEEE Visualization Conference (VIS) - Poster, 2016. paper
Alexander Rind, Wolfgang Aigner, Markus Wagner, Silvia Miksch, Tim Lammarsch, "Task Cube: A Three-Dimensional Conceptual Space of User Tasks in Visualization Design and Evaluation", Information Visualization, vol. 15, pp. 288-300, 2016. paper
Bilal Alsallakh, Luana Micallef, Wolfgang Aigner, Helwig Hauser, Silvia Miksch, Peter Rodgers, "The State-of-the-Art of Set Visualization", Computer Graphics Forum, vol. 35, pp. 234–260, 2016. paper
Theresia Gschwandtner, Markus Bögl, Paolo Federico, Silvia Miksch, "Visual Encodings of Temporal Uncertainty: A Comparative User Study", IEEE Transactions on Visualization and Computer Graphics, vol. 22, pp. 539 - 548, 2016. paper