Christian Bors

Function
Former
Address

Favoritenstraße 9-11, A-1040 Vienna, Austria

TU Wien Addressbook

Research

  • Visualizing Data Quality
    • Data Quality Metrics - Indicating the Quality of a Data Set through providing overview information of specific data characteristics
    • Time-oriented Data Cleansing - Exploiting the specifics of time-oriented data sets to inform users about specialized quality information and cleansing operations
  • Provenance from Data Quality Assessment
    • ​Data Cleansing and Profiling Operations
    • Development of a Data Set
  • Development of robust visualization techniques fitted for providing overview information of tabular data sets
  • Visualization of Uncertainty
    • Quantification of implicit uncertainty information
    • Development of visualization techniques for types of uncertainty

Technical Interests

  • Development
    • Web-Development - JS, AngularJS, D3, ...
    • Java, Mobile Development
    • Visualization in Web-Environments
  • Data
    • ​Uni- and multivariate time series and time-oriented data
    • Open data initiatives
    • Personal Data - private data gathered from fitness tracking, manual logging (personal health)
  • Applications
    • ​Data Transformation Applications
    • Cloud/Web Applications
    • Collaboration-oriented environments
    • Uncertainty aware visualizations
    • Visual interfaces for segmenting and labeling time series

Student Projects

If you are interested in the topics shortly outlined above, please contact me and we will arange a personal meeting to talk about ideas how you can contribute and complete your Master's or Bachelor's thesis.

  • A Visual Approach for Exploring Quality Problems of Multivariate and Time-Oriented Data
    Duration: Feb 2014 - Oct 2016
    Code: https://github.com/zietho/ieg-dqvis
  • Integrating dedicated time-oriented data transformations into OpenRefine
    Duration: Feb 2015 - Jan 2017
    Code: github

Research profile

Short Bio

<p><span style="color: rgb(73, 73, 73);">Visualizing Data Quality</span></p><p><span style="color: rgb(73, 73, 73);">Data Quality Metrics - Indicating the Quality of a Data Set through providing overview information of specific data characteristics</span></p><p><span style="color: rgb(73, 73, 73);">Time-oriented Data Cleansing - Exploiting the specifics of time-oriented data sets to inform users about specialized quality information and cleansing operations</span></p><p><br></p><p><span style="color: rgb(73, 73, 73);">Provenance from Data Quality Assessment</span></p><p><span style="color: rgb(73, 73, 73);">¿Data Cleansing and Profiling Operations</span></p><p><span style="color: rgb(73, 73, 73);">Development of a Data Set</span></p><p><span style="color: rgb(73, 73, 73);">Development of robust visualization techniques fitted for providing overview information of tabular data sets</span></p>

Publications

Christian Bors, "Facilitating Data Quality Assessment Utilizing Visual Analytics: Tackling Time, Metrics, Uncertainty, and Provenance", Institute of Visual Computing and Human-Centered Technology, vol. PhD, Dr.-techn., 2020.
Christian Bors, Christian Eichner, Silvia Miksch, Christian Tominski, Heidrun Schumann, Theresia Gschwandtner, "Exploring Time Series Segmentations Using Uncertainty and Focus+Context Techniques", EuroVis 2020, 2020.
An uncertainty quantification cube for multivariate time series Christian Bors, Jürgen Bernard, Markus Bögl, Theresia Gschwandtner, Jörn Kohlhammer, Silvia Miksch, "Quantifying Uncertainty in Multivariate Time Series Pre-Processing", EuroVis Workshop on Visual Analytics (EuroVA), 2019.
Jürgen Bernard, Marco Hutter, Heiko Reinemuth, Hendrik Pfeifer, Christian Bors, Jörn Kohlhammer, "Visual-Interactive Preprocessing of Multivariate Time Series Data", Computer Graphics Forum, vol. 38, pp. 11, 2019. paper
The Quality Flow and Provenance Graph views of the Data Quality Provenance Explorer. Christian Bors, Theresia Gschwandtner, Silvia Miksch, "Capturing and Visualizing Provenance From Data Wrangling", IEEE Computer Graphics and Applications, vol. 39, pp. 15, 2019.
Iterative refinement of the provenance task abstraction framework. Christian Bors, John Wenskovitch, Michelle Dowling, Simon Attfield, Leilani Battle, Alex Endert, Olga Kulyk, Robert Laramee, "A Provenance Task Abstraction Framework", IEEE Computer Graphics and Applications, vol. 39, pp. 15, 2019.
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
Jürgen Bernard, Christian Bors, Markus Bögl, Christian Eichner, Theresia Gschwandtner, Silvia Miksch, Heidrun Schumann, Jörn Kohlhammer, "Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series", EuroVis Workshop on Visual Analytics (EuroVA) 2018, pp. 49–53, 2018.
Christian Bors, Theresia Gschwandtner, Silvia Miksch, "Visually Exploring Data Provenance and Quality of Open Data", EuroVis 2018 - Posters, pp. 9–11, 2018.
Markus Bögl, Christian Bors, Theresia Gschwandtner, Silvia Miksch, "Uncertainty types in segmenting and labeling time series data", , 2018.
Markus Bögl, Christian Bors, Theresia Gschwandtner, Silvia Miksch, "Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data", , 2018. paper
Christian Bors, Markus Bögl, Jürgen Bernard, Theresia Gschwandtner, Silvia Miksch, "Quantifying Uncertainty in Time Series Data Processing", , 2018.
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
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.
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.