Abstract
With an ever-growing amount of collected data, the importance of visualization as an analysis component is growing in concert. The creation of good visualizations often doesn't happen in one step but is rather an iterative and exploratory process. However, this process is currently not well supported in most of the available visualization tools and systems. Visualization authors are forced to commit prematurely to particular design aspects of their creations, and when exploring potential variant visualizations, they are forced to adopt ad hoc techniques such as copying code snippets or keeping a collection of separate files.
We propose variational visualizations as a model supporting open-ended exploration of the design space of information visualization. Together with that model, we present a prototype implementation in the form of a domain-specific language embedded in Purescript.
- Thorsten Berger, Markus Völter, Hans Peter Jensen, Taweesap Dangprasert, and Janet Siegmund. 2016. Efficiency of Projectional Editing: A Controlled Experiment. In ACM SIGSOFT Int. Symp. on Foundations of Software Engineering. 763-774. Google Scholar
Digital Library
- Jacques Bertin. 1999. Semiology of Graphics: Diagrams, Networks, Maps. Morgan Kaufmann Publishers Inc. English translation.Google Scholar
- Michael Bostock and Jeffrey Heer. 2009. Protovis: A Graphical Toolkit for Visualization. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009), 1121-1128. Google Scholar
Digital Library
- Michael Bostock, Vadim Ogievetsky, and Jeffrey Heer. 2011. D3: Data-Driven Documents. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2301-2309. Google Scholar
Digital Library
- D. J. Duke, R. Borgo, M. Wallace, and C. Runciman. 2009. Huge Data But Small Programs: Visualization Design via Multiple Embedded DSLs. In Practical Aspects of Declarative Languages, Andy Gill and Terrance Swift (Eds.). 31-45. Google Scholar
Digital Library
- Martin Erwig and Karl Smeltzer. 2018. Variational Pictures. In Int. Conf. on the Theory and Application of Diagrams (LNAI 10871). 55-70.Google Scholar
- Martin Erwig and Eric Walkingshaw. 2011. The Choice Calculus: A Representation for Software Variation. ACM Transactions on Software Engineering and Methodology 21, 1, Article 6 (2011), 27 pages. Google Scholar
Digital Library
- Björn Hartmann, Loren Yu, Abel Allison, Yeonsoo Yang, and Scott R. Klemmer. 2008. Design As Exploration: Creating Interface Alternatives Through Parallel Authoring and Runtime Tuning. In ACM Symp. on User Interface Software and Technology. 91-100. Google Scholar
Digital Library
- Jeffrey Heer and Michael Bostock. 2010. Declarative Language Design for Interactive Visualization. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1149-1156. Google Scholar
Digital Library
- Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melançon. 2008. Visual Analytics: Definition, Process, and Challenges. In Information Visualization: Human-Centered Issues and Perspectives, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). 154-175. Google Scholar
Digital Library
- Ralf Lämmel and Simon Peyton Jones. 2003. Scrap Your Boilerplate: A Practical Design Pattern for Generic Programming. In ACM SIGPLAN Int. Workshop on Types in Language Design and Implementation. 26-37. Google Scholar
Digital Library
- Peter Rautek, Stefan Bruckner, M Eduard Gröller, and Markus Hadwiger. 2014. ViSlang: A system for interpreted domain-specific languages for scientific visualization. IEEE Transactions on Visualization and Computer Graphics 20, 12 (2014), 2388-2396.Google Scholar
Cross Ref
- David Reinsel, John Gantz, and John Rydning. 2017. Data Age 2025: The Evolution of Data to Life-Critical. Technical Report. IDC.Google Scholar
- Karl Smeltzer, Martin Erwig, and Ronald Metoyer. 2014. A Transformational Approach to Data Visualization. In Int. Conf. on Generative Programming: Concepts and Experiences. 53-62. Google Scholar
Digital Library
- Michael Terry and Elizabeth D. Mynatt. 2002. Side Views: Persistent, On-demand Previews for Open-ended Tasks. In ACM Symp. on User Interface Soft. and Tech. 71-80. Google Scholar
Digital Library
- Michael Terry, Elizabeth D. Mynatt, Kumiyo Nakakoji, and Yasuhiro Yamamoto. 2004. Variation in Element and Action: Supporting Simultaneous Development of Alternative Solutions. In SIGCHI Conf. on Human Factors in Comp. Systems. 711-718. Google Scholar
Digital Library
- Edward R. Tufte. 2001. The Visual Display of Quantitative Information (2nd ed.). Graphics Press LLC.Google Scholar
- Jarke J. van Wijk. 2005. The Value of Visualization. In IEEE Visualization. 79-86.Google Scholar
- Hadley Wickham. 2016. ggplot2: Elegant Graphics for Data Analysis (2nd ed.). Springer. Google Scholar
Digital Library
- Leland Wilkinson. 2006. The Grammar of Graphics. Springer Science & Business Media. Google Scholar
Digital Library
- Brent A. Yorgey. 2012. Monoids: Theme and Variations (Functional Pearl). In Haskell Symposium. 105-116. Google Scholar
Digital Library
Index Terms
A domain-specific language for exploratory data visualization
Recommendations
A domain-specific language for exploratory data visualization
GPCE 2018: Proceedings of the 17th ACM SIGPLAN International Conference on Generative Programming: Concepts and ExperiencesWith an ever-growing amount of collected data, the importance of visualization as an analysis component is growing in concert. The creation of good visualizations often doesn't happen in one step but is rather an iterative and exploratory process. ...
Exploratory Visualization of Surgical Training Databases for Improving Skill Acquisition
A new visualization system analyzes multidimensional surgical performance databases of information collected via emerging surgical robot and simulator technologies. In particular, it has visualized force, position, rotation, and synchronized video data ...
TimeLine and visualization of multiple-data sets and the visualization querying challenge
Data in its raw form can potentially contain valuable information, but much of that value is lost if it cannot be presented to a user in a way that is useful and meaningful. Data visualization techniques offer a solution to this issue. Such methods are ...







Comments