A Bifocal View

Ameyap
Sparks of Innovation: Stories from the HCIL
8 min readOct 15, 2020

Data visualization research of the past and present.

A multilevel pie chart — “The Apples of my eye”

By Deepthi Raghunandan and Ameya Patil

Recently, the Association of Computing Machinery (ACM) decided to make its historical SIGCHI video archive available online. The CHI conference, organized by SIGCHI, has been the main stage for breakthrough ideas and technology in the field of Human-Computer Interaction (HCI) and other fields such as virtual reality or visualization for decades. This archive includes videos of the CHI conference from 1983 to 2002 including demonstrations and talks that were recorded on magnetic tapes and were played via a VHS player. To bring these hidden treasures to light, Dr. Catherine Plaisant, of the University of Maryland’s iSchool, and Ms. Nat DeMenthon, a PhD student at the University of Maryland, took up the monumental task of digitizing the archive, painstakingly reviewing decades of conference proceedings, and obtaining copyright permissions from the authors. This effort is a part of the Historical CHI Video Project and the videos will be made available on the ACM Digital Library with the aim of spreading awareness of the work of HCI pioneers and to inspire future research.

Focus + Context

We, as students actively conducting research in HCI, were invited to view and leverage these archives for our own research in Data Visualization. From this period between 1983 and 2002, there are around 400 demos and 40 odd videos pertaining to the area of data visualization and we viewed a dozen of them which seemed most relevant to our studies. Looking through the digital video archive was eye opening! Many of these videos were made before we were born; we had erroneously assumed that many of the problems being addressed by the researchers of the past were kind of irrelevant. One example is the 1983 video on “The Bifocal Display” by Robert Spence (Imperial College London) and Mark Apperley (University of Waikato, New Zealand) [1]. The concept of bifocal display was invented much earlier than we thought and it was interesting to see how it is still relevant today.

1983: The Bifocal Display — the fundamental concept behind a lot of visualization/display techniques

While scanning a newspaper, our eyes can pretty easily focus on reading particular columns and still be aware of the other articles. Digital screens lack this capacity, because they allow the reader to only view a ‘window’ at a time, and that’s where the bifocal display concept proved useful. Though it seems simple and intuitive, it is this foundational research that qualifies many interface elements we take for granted today — for example, the flipbook type shuffle UI in Apple Music.

The effect of this work on subsequent research became clear as we explored more of the ACM archive. In 1987, Kim Fairchild (Boeing Corporation), Steven Poltrock (Boeing Corporation), and George Furnas (University of Michigan, Ann Arbor) implemented a literal bifocal view to imply a 3D space on a system called SemNet [14] — creating the sharpest focus on elements “closest” to the viewer. The 3D space is used to help users explore high-level concepts and their relationships as a graph — a foundational technique that is being used in more than one software system today, especially the ontology visualization tools like Ontodia [9], KC-Viz [8] and OntoSphere [14].

In 1993, Marc Brown(DEC Systems Research), James Meehan (DEC System Research) and Manojit Sarkar (Brown University) expanded on bifocal displays by implementing a fish-eye view [2] to make graph browsing tasks easier. They allowed the focused area of the graph to enlarge to fit most of the screen space for better viewing. In ’95, Ramana Rao (Xerox PARC) and Stuart Card (Xerox PARC) put the fish-eye effect to use in a tool for table visualization called Table Lens [5]. The system allowed viewers to focus on particular sections of a table; keeping the overview of the entire dataset and allowing selected rows to show more details. They even demonstrate a means to encode bar graphs directly into table cells.

It comes as no surprise that these innovations continue to have a serious impact on industry — particularly in today’s visualizations tools like TourDino [11] , MetricVis [12] and Tableau [13]. We will be thinking about Dr. Robert Spence and Dr. Mark Apperley the next time we explore visualization details with a focus of interest.

Interactive Data Analysis

We also found that contemporary e-commerce websites like Kayak and Amazon, or data analysis dashboards like Kibana, had their roots in some of the landmark projects of the 1980s and 1990s.

1992: Home Finder — dynamically querying a database for faster insight generation, is ubiquitous today

For example, the idea of dynamically querying a database was introduced in the Home Finder and Film Finder by Ben Shneiderman and his students Chris Williamson and Christopher Ahlberg respectively (from the University of Maryland). ‘Dynamap’ by Catherine Plaisant and Vinit Jain (University of Maryland) took it one step further by automatically generating interactive controls based on the dataset. It was a revelation to see how the most simple data querying widgets like sliders, check boxes, and interactive maps, became more sophisticated over the years and are now embraced by almost all database querying applications today. Programming libraries like Bokeh and Dash have been created to design interactive dashboards and websites that have their roots in these early works.

Visualization Authoring

The field of information visualization saw tools being created to aid in the creation of visualizations for program and data analysis. As early as 1983, HCI researchers were discussing multi-view screens for managing and controlling visualizations. In the “Program Visualization” video by Christopher Herot, Gretchen Brown, Richard Carling, and David Kramlich (all from the Computer Corporation of America) [3], we see window-related controls categorized into graphical display cards to provide different context. ‘Visage’ [4] by Peter Lucas (MAYA Design Group), Cristina Gomberg (MAYA Design Group) and Steven Roth (CMU), was an early attempt to create a simple tool to allow users to create visualizations like bar charts and scatter plots by simply dragging and dropping attributes from a database onto a canvas. Jock Mackinlay (Stanford) had come up with guidelines on automating the visualization creation process prior to this in 1986 and today we use a more sophisticated version of the tool called ‘Tableau’ [13]. The pioneers of the past did not just stop at automating visualization creation for business analytics; they also accommodated the storytellers and narrators, who were more interested in breaking free from the templates of bar graphs and line charts.

1995: SageTools — drag and drop attributes to create visualizations

In 1995, ‘SageTools’ [6] was built by Steven Roth, John Kolojejchick, Joe Mattis, Mei Chuah, Jade Goldstein, and Octavio Juarez at CMU. It gives graphic designers a lot of creative freedom to build eye-catching visualizations, while reducing manual labour. Once again, we see parallels to the ‘Adobe Illustrator’ of today. I was amazed that many contemporary applications continue to build on the work that was introduced more than 20 years ago.

It’s difficult for us to illustrate the diversity and richness present in the SIGCHI Video Archive. The experiential nature of video has helped us connect with researchers of the past. Looking through these videos, we have found that much of the work developed at SIGCHI over the years has become part of our daily lives. Understanding the history of these ideas provided plenty of inspiration for our own research, and we believe it will help all the budding HCI researchers out there too!

References

[1] M. D. Apperley, I. Tzavaras, and R. Spence. A bifocal display technique for data presentation. In Proceedings of the European Computer Graphics Conference and Exhibition, 1982. doi: 10.2312/eg.19821002

[2] M. H. Brown, J. R. Meehan, and M. Sarkar. Browsing graphs using a fisheye view. In Proceedings of the ACM SIGCHI/INTERACT International Conference on Human-Computer Interaction, p. 516. ACM, 1993. doi: 10.1145/169059.169474

[3] D. Kramlich, G. P. Brown, R. T. Carling, and C. F. Herot. Program visual-ization: Graphics support for software development. In Proceedings of the Design Automation Conference, pp. 143–149. ACM/IEEE, 1983.

[4] P. Lucas, C. C. Gomberg, and S. F. Roth. Visage: Dynamic information exploration. In Companion of the ACM Conference on Human Factors in Computing Systems, pp. 19–20. ACM, 1996. doi: 10.1145/257089.257107

[5] R. Rao and S. K. Card. Exploring large tables with the table lens. In Companion of the ACM Conference on Human Factors in Computing Systems, pp. 403–404. ACM, 1995. doi:10.1145/223355.223745

[6] S. F. Roth, J. Kolojejchick, J. Mattis, M. C. Chuah, J. Goldstein, and O. Juarez. SAGE tools: a knowledge-based environment for designing and perusing data visualizations. In Proceedings of the Conference on Human Factors in Computing Systems, pp. 27–28. ACM, 1994. doi: 10.1145/259963.259992

[7] B. Shneiderman, C. Williamson, and C. Ahlberg. Dynamic queries: Database searching by direct manipulation. In Proceedings of the ACM Conference on Human Factors in Computing Systems, pp. 669–670, 1992. doi: 10.1145/142750.143082

[8] E. Motta, S. Peroni, N. Li, and M. d’Aquin, Mathieu, J.-M. Gomez-Perez, V. Mendez, F. Zablith. KC-Viz: A Novel Approach to Visualizing and Navigating Ontologies. In Proceedings of the International Semantic Web Conference, pp 470–486, 2011.

[9] D. Mouromtsev, D. Pavlov, Y. Emelyanov, A. Morozov, D. Razdyakonov, and M. Galkin. The simple, web-based tool for visualization and sharing of semantic data and ontologies. In Posters and Demonstrations track of the International Semantic Web Conference, 2015.

[10] K. Eckelt, P. Adelberger, T. Zichner, A. Wernitznig, and M. Streit. TourDino: A Support View for Confirming Patterns in Tabular Data. In Proceedings of the EuroVis Workshop on Visual Analytics, pp. 7–11, 2019.

[11] J. Zhao, M. Karimzadeh, L. S. Snyder, C. Surakitbanharn, Z. C. Qian and D. S. Ebert. MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies. IEEE Transactions on Visualization and Computer Graphics, 26(1):1193–1203, 2020, doi: 10.1109/TVCG.2019.2934603.

[12] J. Mackinlay, P. Hanrahan, C. Stolte. Show Me: Automatic Presentation for Visual Analysis. IEEE Transactions on Visualization and Computer Graphics, 13(6):1137–44, 2007. doi: 10.1109/TVCG.2007.70594.

[13] K. M. Fairchild, S. E. Poltrock, and G. W. Furnas. SemNet: three-dimensional graphic representations of large knowledge bases. In Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 190–206, 1999.

[14] A. Bosca, D. Bonino, and P. Pellegrino. Ontosphere: more than a 3dontology visualization tool. In P. Bouquet and G. Tummarello, eds.,SWAP2005 — Semantic Web Applications and Perspectives, Proceedings of the 2ndItalian Semantic Web Workshop, University of Trento, Trento, Italy, 14–16December 2005, vol. 166 ofCEUR Workshop Proceedings. CEUR-WS.org,2005

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