CVAST - Centre for Visual Analytics Science and Technology

Submitted by Bilal Alsallakh on Thu, 3. Jan 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

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, Heidrun Schuman, Jürgen Bernard, Thorsten May, Markus Bögl, Silvia Miksch, Jörn Kohlhammer, Martin Röhlig, Bilal Alsallakh, "Enhancing Time Series Segmentation and Labeling Through the Knowledge Generation Model", Poster Proceedings of the Eurographics Conference on Visualization (EuroVis 2015), pp. 3, 2015.
Christian Bors, Theresia Gschwandtner, Silvia Miksch, "QualityFlow: Provenance Generation from Data Quality", Proceedings of the Eurographics Conference on Visualization (EuroVis) - Posters 2015, pp. 3, 2015. paper
Roger Leite, Theresia Gschwandtner, Silvia Miksch, Erich Gstrein, Johannes Kuntner, "Visual Analytics for Fraud Detection and Monitoring", Poster Proceedings of the IEEE Visualization Conference 2015, 2015. paper
Wolfgang Aigner, Silvia Miksch, Heidrun Schumann, Christian Tominski, "Visualization Techniques for Time-Oriented Data", Interactive Data Visualization: Foundations, Techniques, and Applications, pp. 253–284, 2015. paper Book webpage
Markus Bögl, Wolfgang Aigner, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Silvia Miksch, Alexander Rind, "Visually and Statistically Guided Imputation of Missing Values in Univariate Seasonal Time Series", Poster Proceedings of the IEEE Visualization Conference 2015, 2015. paper Preview Video
Martin Röhlig, Martin Luboschik, Markus Bögl, Frank Krüger, Bilal Alsallakh, Silvia Miksch, Thomas Kirste, Heidrun Schumann, "Supporting Activity Recognition by Visual Analytics", Proceedings of the IEEE Conference on Visual Analytics Science and Technology, 2015. paper Teaser
Markus Bögl, Wolfgang Aigner, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Silvia Miksch, Alexander Rind, "Integrating Predictions in Time Series Model Selection", Proceedings of the EuroVis Workshop on Visual Analytic, EuroVA, pp. 73-77, 2015. paper
Peter Bodesinsky, Bilal Alsallakh, Theresia Gschwandtner, Silvia Miksch, "Exploration and Assessment of Event Data", Sixth International EuroVis Workshop on Visual Analytics (EuroVA) 2015, pp. 5, 2015. paper
Bilal Alsallakh, Markus Bögl, Theresia Gschwandtner, Silvia Miksch, Bilal Esmael, Arghad Arnaout, Gerhard Thonhauser, Philipp Zöllner, "A Visual Analytics Approach to Segmenting and Labeling Multivariate Time Series Data", EuroVis Workshop on Visual Analytics (EuroVA), pp. 31-35, 2014. paper
Paolo Federico, Albert Amor-Amorós, Silvia Miksch, "Knowledge-assisted EHR visualization for cohorts", Proceedings of the IEEE Vis Workshop on Visualizing Electronic Health Record Data (EHRVis 2014), 2014. paper
Bilal Alsallakh, Luana Micallef, Wolfgang Aigner, Helwig Hauser, Silvia Miksch, Peter Rodgers, "Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges", Eurographics conference on Visualization (EuroVis)– State of The Art Reports, pp. 1-21, 2014. paper Survey Browser
Peter Bodesinsky, Bilal Alsallakh, Theresia Gschwandtner, Silvia Miksch, "Visual Process Mining: Event Data Exploration and Analysis", Poster Proceedings of the IEEE Visualization Conference (VIS), 2014. paper
Theresia Gschwandtner, Wolfgang Aigner, Silvia Miksch, Johannes Gärtner, Simone Kriglstein, Margit Pohl, Nikolaus Suchy, "TimeCleanser: A Visual Analytics Approach for Data Cleansing of Time-Oriented Data", 14th International Conference on Knowledge Technologies and Data-driven Business (i-KNOW 2014), pp. 1-8, 2014.
Christian Bors, Theresia Gschwandtner, Silvia Miksch, Johannes Gärtner, "QualityTrails: Data Quality Provenance as a Basis for Sensemaking", Proceedings of the IEEE VIS Workshop on Provenance for Sensemaking, pp. 1–2, 2014. paper
Bilal Alsallakh, Allan Hanbury, Helwig Hauser, Silvia Miksch, Andreas Rauber, "Visual Methods for Analyzing Probabilistic Classification Data", IEEE Transactions on Visualization and Computer Graphics, vol. 20, pp. 1703--1712, 2014. paper Examples with public classification datasets The visual and interaction metaphors
Markus Bögl, Wolfgang Aigner, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Silvia Miksch, Alexander Rind, "Visual Analytics Methods to Guide Diagnostics for Time Series Model Predictions", Proceedings of the 2014 IEEE VIS Workshop on Visualization for Predictive Analytics, 2014. paper
Margit Pohl, Florian Scholz, Simone Kriglstein, Bilal Alsallakh, Silvia Miksch, "Evaluating the Dot-Based Contingency Wheel: Results from a Usability and Utility Study", HCI International, pp. 76--86, 2014.
Bilal Alsallakh, Silvia Miksch, Andreas Rauber, "Towards a Visualization of Multi-faceted Search Results", Workshop on Knowledge Maps and Information Retrieval (KMIR), vol. 1311, pp. 4, 2014. paper
Tim Lammarsch, Wolfgang Aigner, Silvia Miksch, Alexander Rind, "Showing Important Facts to a Critical Audience by Means Beyond Desktop Computing", Death of the Desktop - Workshop co-located with IEEE VIS 2014, 2014. paper
Daniel Archambault, James Abello, Jessie Kennedy, Stephen Kobourov, Kwan-Liu Ma, Silvia Miksch, Chris Muelder, Alexandru Telea, "Temporal Multivariate Networks", Multivariate Network Visualization, pp. 151-174, 2014. paper
Albert Amor-Amorós, Paolo Federico, Silvia Miksch, "TimeGraph: a Data Management Framework for Visual Analytics of Large Multivariate Time-Oriented Networks", Poster Proceedings of the IEEE Visualization Conference (VIS), 2014. paper TimeGraph teaser
, "Knowledge Representation for Health Care, 6th International Workshop, KR4HC 2014, held as part of the Vienna Summer of Logic, VSL 2014, Vienna, Austria, July 21, 2014. Revised Selected Papers", Lecture Notes in Computer Science, vol. 8903, pp. 175, 2014. paper
Martin Röhlig, Martin Luboschik, Heidrun Schuman, Markus Bögl, Bilal Alsallakh, Silvia Miksch, "Analyzing Parameter Influence on Time-Series Segmentation and Labeling", Poster Proceedings of the IEEE Visualization Conference (VIS), 2014. paper Preview