Visualizing temporal data CPSC A. Butt / Feb. 24 '09

Overview First, a review of "Lifelines" (1996) Movie / Samples from Lifelines Next, a review of "Artifacts of the Presence Era" (1996) Samples from Artifacts Comparison of Approaches Other readings on "temporal frameworks" Project implications References

Lifelines Developed in the mid 1990's by collaborators at the Human- Computer Interactions Lab (HCIL) Originally developed for youth criminal case files - extended to medical records / personal histories Uses time lines - common graphic representation Time lines are for navigation / orientation of historical events –Parallelism used for correlation Adds visual cues of line colour, width to highlight data attributes Adds filtering, zoom and concurrent textual panes

Lifelines And now an (abbreviated) historical newsreel

Artifacts of the Presence Era Developed in 2003 by collaborators at the Social Media Group at the MIT Media Lab "Like the visible layers of a canyon, witnesses to sedimentary accumulation over time, the layers in Artifacts of the Presence Era tell us a story of past events. Here, the images and sounds produced in the ICA gallery are captured and then visualized as a growing, organic landscape that serves as a historical record. Like its natural counterpart, this process reveals long- term patterns (the rhythm of night and day, periods of great activity or empty silence), while retaining occasionally serendipitous, but often mundane, samples of the passage of life." ( Uses geological metaphor - uncommon graphic representation Visualization process reflects time (colour/light variation) and concurrent activity level (acoustic data)

Artifacts of the Presence Era

Comparison of Approaches Lifelines –purposed for navigation (by experts) –timeline to express history, icon to express event –categorization by colour, saturation, line characteristics –zoom/filter to control data clutter –limits on data set (larger = clutter) Artifacts –purposed for art museum installation (evocative souvenirs) –time by layer, with compression –categorization by audio/luminance (not understood by audience) –limits on data resolution (compression = lossy - fossils?)

Other readings Differences in approach are to be expected Yet fundamentals are constant: "a property is temporal if successive values have meaning" (Daassi et al 2004) Visualization guided by the point that data and time are fused

Other readings Move away from preconceived visualization processes Start with careful consideration of time and data set the basis for representation (Aigner et al 2007) - let this drive the visualization

Project Implications Motivation driven by research area –decisions with environmental effects "live" in time, typical focus is forward looking / branching time –does regulatory policy drive the nature of time / data that in turn drives the applicability of visualization techniques? –does the visualization technique drive analytical thinking and therefore affect policy decisions?

References Aigner, W., Miksch, S., Müller, W., Schumann, H., and Tominski, C Visualizing time- oriented data-A systematic view. Comput. Graph. 31, 3 (Jun. 2007), DOI= Artifacts of the Presence Era: Using Information Visualization to Create an Evocative Souvenir. Fernanda Viegas, Ethan Perry, Ethan Howe, Judith Donath. In the proceedings of the IEEE symposium of Information Visualization, InfoVis’04. InfoVis 2004, in Austin, TX. Daassi, Chaouki, Laurence Nigay, and Marie-Christine Fauvet. “A taxomony of temporal data visualization techniques.” Information-Interaction-Intelligence 5.2 (2005). Plaisant, P. and Rose, A. (March 1996). Exploring LifeLines to Visualize Patient Records. A short version of this report appeared as a poster summary in 1996 American Medical Informatic Association Annual Fall Symposium (Washington, DC, Oct , 1996), pp. 884, AMIA, Bethesda MD. HCIL-96-04, CS-TR-3620, CAR-TR-819