Eser Kandogan
ABSTRACT
Understanding what insights people draw from data visualizations is critical for human-in-the loop analytics systems to facilitate mixed-initiative analysis. In this paper we present results from a large user study on insights extracted from commonly used charts. We report several patterns of insights we observed and analyze their semantic structure to identify key considerations towards a unified formal representation of insight, human or computer generated. We also present a model of insight generation process, where humans and computers work cooperatively, building on each other's knowledge, where a common representation acts as the currency of interaction. While not going as far as proposing a formalism, we point to a few potential directions for representing insight. We believe our findings could also inform the design of novel human-in-the-loop analytics systems.
- Matthew Brehmer and Tamara Munzner. 2013. A multi-level typology of abstract visualization tasks. Visualization and Computer Graphics, IEEE Transactions on 19, 12 (2013), 2376--2385. Google Scholar
Digital Library
- Ulrich Engelke and Eser Kandogan. 2016. Towards an Algebra for the Visual Analytics Design Process. In Visual Analytics Science and Technology (VAST), Poster Paper. IEEE, 1--2.Google Scholar
- Tong Gao, Mira Dontcheva, Eytan Adar, Zhicheng Liu, and Karrie G. Karahalios. 2015. DataTone: Managing Ambiguity in Natural Language Interfaces for Data Visualization. In Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (UIST '15). ACM, New York, NY, USA, 489--500. Google ScholarDigital Library
- David Gotz and Michelle X Zhou. 2009. Characterizing users' visual analytic activity for insight provenance. Information Visualization 8, 1 (2009), 42--55. Google ScholarDigital Library
- Tera Marie Green, William Ribarsky, and Brian Fisher. 2009. Building and Applying a Human Cognition Model for Visual Analytics. Information Visualization 8, 1 (Jan. 2009), 1--13. Google ScholarDigital Library
- Hua Guo, Steven R Gomez, Caroline Ziemkiewicz, and David H Laidlaw. 2016. A Case Study Using Visualization Interaction Logs and Insight Metrics to Understand How Analysts Arrive at Insights. Visualization and Computer Graphics, IEEE Transactions on 22, 1 (2016), 51--60.Google Scholar
- Jeffrey Heer and Michael Bostock. 2010. Declarative language design for interactive visualization. Visualization and Computer Graphics, IEEE Transactions on 16, 6 (2010), 1149--1156. Google ScholarDigital Library
- E. Kandogan. 2012. Just-in-time annotation of clusters, outliers, and trends in point-based data visualizations. In 2012 IEEE Conference on Visual Analytics Science and Technology (VAST). 73--82. Google ScholarDigital Library
- Eser Kandogan and Hanseung Lee. 2016. A Grounded Theory Study on the Language of Data Visualization Principles and Guidelines. Electronic Imaging 2016, 16 (2016), 1--9.Google ScholarCross Ref
- E. Kandogan, M. Roth, C. Kieliszewski, F. Ozcan, B. Schloss, and M. T. Schmidt. 2013. Data for All: A Systems Approach to Accelerate the Path from Data to Insight. In 2013 IEEE International Congress on Big Data. 427--428. Google ScholarDigital Library
- Eser Kandogan, Mary Roth, Peter Schwarz, Joshua Hui, Ignacio Terrizzano, Christina Christodoulakis, and Renée J Miller. 2015. LabBook: Metadata-driven social collaborative data analysis. In Big Data (Big Data), 2015 IEEE International Conference on. IEEE, 431--440. Google ScholarDigital Library
- Gordon Kindlmann and Carlos Scheidegger. 2014. An algebraic process for visualization design. Visualization and Computer Graphics, IEEE Transactions on 20, 12 (2014), 2181--2190.Google Scholar
- M. Lichman. 2013. UCI ML Repository. (2013). http://archive.ics.uci.edu/mlGoogle Scholar
- Ronald Metoyer, Bongshin Lee, Nathalie Henry Riche, and Mary Czerwinski. 2012. Understanding the Verbal Language and Structure of End-user Descriptions of Data Visualizations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '12). ACM, New York, NY, USA, 1659--1662. Google ScholarDigital Library
- Chris North. 2006. Toward measuring visualization insight. IEEE computer graphics and applications 26, 3 (2006), 6--9. Google ScholarDigital Library
- Dominik Sacha, Andreas Stoffel, Florian Stoffel, Bum Chul Kwon, Geoffrey Ellis, and Daniel A Keim. 2014. Knowledge generation model for visual analytics. IEEE transactions on visualization and computer graphics 20, 12 (2014), 1604--1613.Google Scholar
- Purvi Saraiya, Chris North, and Karen Duca. 2005. An insight-based methodology for evaluating bioinformatics visualizations. IEEE transactions on visualization and computer graphics 11, 4 (2005), 443--456. Google ScholarDigital Library
- Hans-Jorg Schulz, Thomas Nocke, Magnus Heitzler, and Heidrun Schumann. 2013. A design space of visualization tasks. Visualization and Computer Graphics, IEEE Transactions on 19, 12 (2013), 2366--2375. Google ScholarDigital Library
- Vidya Setlur, Sarah E. Battersby, Melanie Tory, Rich Gossweiler, and Angel X. Chang. 2016. Eviza: A Natural Language Interface for Visual Analysis. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16). ACM, New York, NY, USA, 365--377. Google ScholarDigital Library
- Jarke J. Van Wijk. 2005. The Value of Visualization. 79--86.Google Scholar
- Leland Wilkinson. 2006. The grammar of graphics. Springer Science & Business Media.Google ScholarDigital Library
- Huahai Yang, Yunyao Li, and Michelle X Zhou. 2014. Understand users comprehension and preferences for composing information visualizations. ACM Transactions on Computer-Human Interaction (TOCHI) 21, 1 (2014), 6. Google ScholarDigital Library
- Ji Soo Yi, Youn ah Kang, John T Stasko, and Julie A Jacko. 2007. Toward a deeper understanding of the role of interaction in information visualization. Visualization and Computer Graphics, IEEE Transactions on 13, 6 (2007), 1224--1231. Google ScholarDigital Library
- Ji Soo Yi, Youn-ah Kang, John T Stasko, and Julie A Jacko. 2008. Understanding and characterizing insights: how do people gain insights using information visualization?. In Proceedings of the 2008 Workshop on BEyond time and errors: novel evaLuation methods for Information Visualization. ACM, 4. Google ScholarDigital Library
- Emanuel Zgraggen, Zheguang Zhao, Robert Zeleznik, and Tim Kraska. 2018. Investigating the Effect of the Multiple Comparisons Problem in Visual Analysis. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Article 479, 12 pages. Google ScholarDigital Library
Index Terms
- Towards a Unified Representation of Insight in Human-in-the-Loop Analytics: A User Study
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