Hello everyone! Welcome to the presentation of our paper "The Power of
Linked Eye Movement Data Visualizations" This is joint work with Michael Burch
Nick Broeks, Lulof Piree, Nynke Boonstra, Paul
Vlaswinkel, Silke Franken, and Vince van Wijk. My name is Günter Wallner and I'm happy to
present this work today on behalf of all my co-authors.
Nowadays, sophisticated technology makes it comparably easy to apply eye tracking
in many different domains. However, data sets and eye movements can
quickly become very large which makes it challenging to analyze
them. In this regard visualizations have become an important part
to explore, analyze, and draw insights from the collected data.
As such different visualizations ranging from heatmaps to scanpaths
have been proposed over time. Relying on a single visualization only can, however,
be limiting as each type of visualization
only provides a certain perspective on the data.
In this work we developed a tool that supports
several linked, interactive visualizations
to be able to inspect the data from different angles.
Our design goals were to create an easy to use,
versatile, tool that can be easily accessed through a web browser.
It should support different types of visualizations
and it should allow the user to also save the analysis progress
and be able to share it with others.
On this slide you can see the graphical user interface of the tool which
consists of two parts, the navigation menu on the left,
and a page of panels on the right. The layout, order, and the amount of
panels can be fully customized. Individual panels are also resizable
and they support their own settings and filter
options. A panel can hold multiple visualizations which are indicated as
tabs at the top left of each panel. A user can choose
which visualization technique to use within a panel
by means of a drop-down menu. This way the
user can juxtapose multiple visualizations to ease comparison tasks,
for instance. The tool also supports a range of
interactions such as different ways to select and filter the data.
Since the views are linked with each other selections, for instance, are
synchronously applied to all the visualizations.
Currently, the tool supports four types of visualizations:
A density plot allows the user to obtain an overview of the
data distribution with the contour lines indicating areas of varying attention.
The three colored rectangles you can see in this example here
represent areas of interest which can be
defined by the user.
The sequence in which the elements were fixated by someone can be reviewed
using a scan-path visualization. Here, the size of the nodes corresponds
to the duration of the fixation and the numbers indicate the
sequence. Furthermore, users can select a bee swarm visualization to observe the
fixations over time. In this case the fixations are represented by small dots
with the ID of the participant. It is animation based and the animation
can be controlled using a slider and different buttons.
And lastly a scarf plot is provided to convey which areas of interest were
observed in which order. It makes use of the
user-defined areas of interest with the areas being encoded with
different colors. To gather first feedback on the
tool and to assess its usefulness we
conducted a short, about 15-minute, online questionnaire
asking participants to explore the tool and solve different
tasks with it. The questionnaire was provided
through Google Forms and it started with a short introduction of the purpose of the
study, a brief explanation of the tool, and we
also obtained consent from the participants at that
stage. Afterward participants were asked
to rate their self-perceived expertise with respect to eye tracking and
visualization. In total, we received 10 responses with almost all
indicating high expertise in visualization
while in terms of eye tracking the sample was a bit
more diverse. Next, the participants had to solve four tasks
with the tool and for each of the task we
required to indicate the solution, the visualizations they have used to
solve it, and how difficult they perceived the task. And
lastly, we asked for general feedback with respect to the
usefulness and the current benefits of drawbacks
of the tool. For the tasks we used an existing dataset from an eye-tracking
study on metro maps of which you can see several different
maps here. Using some of these we asked
participants to solve four tasks as summarized on this slide.
One task focused on identifying highly observed locations,
two focused on comparisons, and one specifically
asked about the temporal aspect. Participants rated most of the tasks on
the upper half of the difficulty scale with 1 being
very difficult and 7 very easy. This suggests
that the tool facilitated solving the
tasks. Among the four, Task 4 was
considered the most difficult one. The table also indicates how many
visualizations were used by how many participants.
Offering multiple views appeared indeed helpful for solving the tasks
as participants frequently relied on two visualizations.
The only exception was Task 4 again, which
asked about the temporal behavior, and here participants relied
mostly on a single visualization only. For Task 1, identifying highly
observed areas the main preferred combination was a
density plot together with a bee swarm. For
comparisons based on the areas of interest
participants mainly combined the density plot with
the scarf plot. For the other two tasks participants
used a range of combinations, so there were no
clear preferences in those cases. Among the four different views, the density
plot and the bee swarm were considered highly useful by the majority of the
respondents. Opinions differed, however, for the scanpath
and the scarf plot, where the ratings were rather uniformly distributed over
the rating range. Qualitative feedback in brief indicated
that participants mainly appreciated that the
tool is easy to understand and interact with and that it
offers multiple linked views with four mentions each. Drawbacks
were mainly with respect to the general usability and here participants
offered several suggestions for improvement. More results can be
found in the paper but in general the user study suggests
the usefulness of providing linked customizable views.
And it also showed multiple ways of moving
forward with the tool. That's it from me. Thanks for joining and I'm happy to take
questions.