Software Demonstration, "Emergent Time" timeline tool

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Software Demonstration,
“Emergent Time” timeline
tool
York, Christopher
cyork@mit.edu
HyperStudio, Massachusetts Institute of
Technology
Trettien, Whitney
HyperStudio, Massachusetts Institute of
Technology
Emergent Time is a prototype collaboration tool
for humanists and social scientists working with
timelines—narrative arrangements of events.
In Emergent Time, timelines are owned by
particular users, and represent the user's
interpretive reading of a series of events.
While an individual timeline “belongs” to a
user, many of the events it interprets may be
shared by other users and interpreted differently
in their timelines. Users construct timelines
individually, using a single form to build on
events others created before them, or to create
new events from scratch. The application thus
balances personal expression and argument
(in the form of individual timelines) with
collaboration and shared work (in the form of
raw events).
Throughout the prototype, clicking on an event
in a timeline will show how other users have
interpreted that particular incident. Thus, one
can read horizontally to follow the argument of
a given timeline, or depth-wise to jump between
different timelines that interpret the same event
from different perspectives.
1. 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.
2. 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.
3. 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.

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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:
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Open-revision wiki
. An open wiki implements
what might be called “last man standing”
collaboration. The last person to edit an article
has license to revise and amend all the others'
work, potentially reshaping it to his own ends.
Of course, wiki history allows others to revise
it back, but this encourages “squatting,” or
continually monitoring an article in order to
control its contents.
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Moderated wiki
. Some wikis establish an
editorial bureaucracy to address these issues.
However, this in effect defers interpretation to
an appointed “expert,” much after the fashion
of a traditional encyclopedia (with the proviso
that the general public can submit material for
editorial consideration).
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Voting systems
. Finally, simple voting
systems that ask users to “rate this article”
suffer from known problems with blind
polling. Anonymity encourages arbitrary
voting; users might vote multiple times or use
incomparable rankings; and the population of
elective voters is self-selecting. By contrast,
Emergent Time's collaboration model is
designed to circumvent such problems, since
users “vote with their feet” by citing one
formulation of an event rather than another
in their timelines, and no one user can
dominate interpretation by being the last to
revise. While this model is relatively new to
digital collaboration tools, it is quite similar to
traditional humanities footnote and endnote
citations. It clearly marks authorship and
source material for a given interpretation,
encourages communal discussion of the
adequacy of an author's evidence, and
holds authors accountable for their votes by
embedding the citations within their work.
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.