timeline

Temporal events, while often discrete, also have interesting relationships within and across times: larger events are often collections of smaller more discrete events (battles within wars; artists' works within a form); events at one point also have correlations with events at other points (a play written in one period is related to its performance over a period of time). Most temporal visualisations, however, only represent discrete data points or single data types along a single timeline: this event started here and ended there; this work was published at this time; this tag was popular for this period. In order to represent richer, faceted attributes of temporal events, we present Continuum. Continuum enables hierarchical relationships in temporal data to be represented and explored; it enables relationships between events across periods to be expressed, and in particular it enables user-determined control over the level of detail of any facet of interest so that the person using the system can determine a focus point, no matter the level of zoom over the temporal space. We present the factors motivating our approach, our evaluation and implementation of this new visualisation which makes it easy for anyone to apply this interface to rich, large-scale datasets with temporal data.

When browsing a long video using a traditional timeline slider control, its effectiveness and precision degrade as a video's length grows. When browsing videos with more frames than pixels in the slider, aside from some frames being inaccessible, scrolling actions cause sudden jumps in a video's continuity as well as video frames to flash by too fast for one to assess the content. We propose a content-aware dynamic timeline control that is designed to overcome these limitations. Our timeline control decouples video speed and playback speed, and leverages video content analysis to allow salient shots to be presented at an intelligible speed. Our control also takes advantage of previous work on elastic sliders, which allows us to produce an accurate navigation control.

We describe Chronicle, a new system that allows users to explore document workflow histories. Chronicle captures the entire video history of a graphical document, and provides links between the content and the relevant areas of the history. Users can indicate specific content of interest, and see the workflows, tools, and settings needed to reproduce the associated results, or to better understand how it was constructed to allow for informed modification. Thus, by storing the rich information regarding the document's history workflow, Chronicle makes any working document a potentially powerful learning tool. We outline some of the challenges surrounding the development of such a system, and then describe our implementation within an image editing application. A qualitative user study produced extremely encouraging results, as users unanimously found the system both useful and easy to use.