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Christian Bors
Christian Bors
Institute of Visual Computing & Human-Centered Technology, TU Wien
Verified email at tuwien.ac.at - Homepage
Title
Cited by
Cited by
Year
Visual‐interactive preprocessing of multivariate time series data
J Bernard, M Hutter, H Reinemuth, H Pfeifer, C Bors, J Kohlhammer
Computer Graphics Forum 38 (3), 401-412, 2019
742019
Capturing and visualizing provenance from data wrangling
C Bors, T Gschwandtner, S Miksch
IEEE computer graphics and applications 39 (6), 61-75, 2019
272019
Visual interactive creation, customization, and analysis of data quality metrics
C Bors, T Gschwandtner, S Kriglstein, S Miksch, M Pohl
Journal of Data and Information Quality (JDIQ) 10 (1), 1-26, 2018
202018
Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series.
J Bernard, C Bors, M Bögl, C Eichner, T Gschwandtner, S Miksch, ...
EuroVA@ EuroVis, 49-53, 2018
172018
A provenance task abstraction framework
C Bors, J Wenskovitch, M Dowling, S Attfield, L Battle, A Endert, O Kulyk, ...
IEEE computer graphics and applications 39 (6), 46-60, 2019
112019
Visual support for rastering of unequally spaced time series
C Bors, M Bögl, T Gschwandtner, S Miksch
Proceedings of the 10th International Symposium on Visual Information …, 2017
112017
Quantifying Uncertainty in Multivariate Time Series Pre-Processing
C Bors, J Bernard, M Bögl, T Gschwandtner, S Miksch, J Kohlhammer
EuroVis Workshop on Visual Analytics 10, 31 - 35, 2019
72019
Visually Exploring Data Provenance and Quality of Open Data.
C Bors, T Gschwandtner, S Miksch
EuroVis (Posters), 9-11, 2018
52018
Qualitytrails: Data quality provenance as a basis for sensemaking
C Bors, T Gschwandtner, S Miksch, J Gärtner
Proceedings of the International Workshop on Analytic Provenance for Sensemaking, 2014
52014
The Effect of Graph Layout on the Perception of Graph Properties.
E Kypridemou, M Zito, M Bertamini
EuroVis (Short Papers), 1-5, 2020
42020
Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data.
M Bögl, C Bors, T Gschwandtner, S Miksch
EuroVis (Posters), 45-47, 2018
42018
Qualityflow: Provenance generation from data quality
C Bors, T Gschwandtner, S Miksch
Poster Proceedings of the EuroGraphics Conference on Visualization, 2014
42014
Exploring Time Series Segmentations Using Uncertainty and Focus+ Context Techniques.
C Bors, C Eichner, S Miksch, C Tominski, H Schumann, T Gschwandtner
EuroVis (Short Papers), 7-11, 2020
22020
Facilitating data quality assessment utilizing visual analytics: tackling time, metrics, uncertainty, and provenance
C Bors
Technische Universität Wien, 2019
12019
4.3 A Novel Approach to Task Abstraction to Make Better Sense of Provenance Data
C Bors, S Attfield, L Battle, M Dowling, A Endert, S Koch, OA Kulyk, ...
Provenance and Logging for Sense Making, 46, 0
1
AProvenance Task
C Bors, J Wenskovitch, M Dowling, S Attfield, L Battle, A Endert, O Kulyk, ...
2019
Uncertainty types in segmenting and labeling time series data
M Bögl, C Bors, T Gschwandtner, S Miksch
2018
Quantifying Uncertainty in Time Series Data Processing
C Bors, M Bögl, J Bernard, T Gschwandtner, S Miksch
2018
Storage and visualization of heterogeneous data from online social networks
C Bors, R Krejci
2013
Vorträge und Posterpräsentationen (ohne Tagungsband-Eintrag)
Y Huang, J Neidhardt, N Contractor
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Articles 1–20