Software Demonstration, “Emergent Time” timeline tool

Overview timelines

The prototype's salient feature is a set of overview timelines, built by analyzing the network of links between timelines and events within the community. These links indicate the most important events for a given topic. For example, a search for “John F Kennedy” might show the most highly-cited events in his life: birth, election, and assassination. To accomplish this, the prototype uses a proprietary implementation of Page & Brin's PageRank algorithm. Events that are linked to in many timelines are likely to be important to the community, and receive a high rank; conversely, timelines that interpret many important events receive a boost in rank. Emergent Time uses these ranks to indicate which event entries are regarded as most authoritative by the general populace of users, and displays them when given a matching topic.

Collaboration strategy

In Emergent Time only the author of a given event can revise it, but the community at large can add source critique comments and propose alternate versions of the event. The design intention was to spark general discussion about whether a given event's description is well-supported by the primary sources cited. Because many versions of a given event may exist, this encourages users to link to the version that is factually best-supported in their own timelines, while passing over those with poor evidentiary support or badly-formulated descriptions. Hence, using an event in one's own timeline constitutes both a signal of interest in the historical incident and a vote of confidence in the event author's scholarship. The collaboration workflow thus serves as a macrocosm of the scholarly publication process, allowing authors and readers to evaluate the evidence in support of a given interpretation, and to “vote with their feet” by citing it rather than another in their own work.

As a result the overview timelines will come to reflect not only which events are most important for the interpretive community, but also which versions of a particular event are most authoritative. This allows overview timelines to present the most influential event entries for a given topic, and to accommodate shifts in communal knowledge as new evidence is found and new interpretations of a given incident become normative.

In contrast to other tools

This collaborative strategy is intended to capture established conventions for historical analysis and source critique, and use the resulting citation networks to construct overview timelines that accurately reflect the community's current normative views. By distributing small bits of knowledge among many event entries, promoting general discussion of the veracity of each, and then allowing users to “vote” for a given version of the facts by including the event in their timeline, it addresses shortcomings in other collaborative digital humanities approaches:

Even with a sparse demo data set, it is clear that the Emergent Time prototype achieves a successful balance between individual work (seen when viewing a particular timeline) and community connections (via the interpretation comparison popup, and the related timelines and related users links). It encourages users to focus on developing their own ideas, while still suggesting points of contact with the wide community — for example, in the event editor, which shows possible base events as the user enters information. The opening page's list of recent community activity is well-suited to draw users into other work and give a sense of liveliness. Most importantly, even for small data sets, it's clear that the overview timelines do actually reflect the community's current notion of the “most important” events.