Hello. My name is Ricardo Langner
and in the next couple of minutes I give you a quick overview of our work MARVIS
Combining Mobile Devices and Augmented Reality for Visual Data Analysis.
This is joint work together with my colleagues
Marc Satkowski, Wolfgang Büschel, and Raimund Dachselt
from the Interactive Media Lab at Technische Universität Dresden.
MARVIS is a conceptual framework in which we explore
the fundamentals of combining common mobile devices such as tablets
with head-mounted Augmented Reality for data visualization.
The basic idea is to use AR
to extend mobile device visualizations
by providing additional 2D and 3D information
around, above, and even between devices.
As one of the core parts of our work,
we present several visualization and interaction concepts,
organized into two categories.
We explain how a single mobile device plus AR can be used for
Overview and Detail
Focus and Context as well as a seamless visualization extension
Also for alternative visualization views
Separated user interface components
and superimposed 3D visualizations.
For cases in which two or more mobile devices are used together,
we describe how AR can
provide visual feedback about the relation between visualizations,
how to assist the combination of visualizations,
and how to support multi-user scenarios.
A second core part of MARVIS is our prototype application,
in which we implemented six different use cases.
The goal behind the first example is to
explore how AR can provide support for navigating within a scatterplot matrix.
For that, we realized 4 different augmentation designs
in which the tablet always shows 1 cell of the matrix.
The first design shows the entire 8 by 8 matrix in AR.
The second design uses thumbnails instead of full-size cells.
A third design uses thumbnails but only shows the row and column specified by the tablet position.
The fourth design uses full-size cells at each side of the tablet.
Here is a thumbnail-like design.
We use 2-finger swipe gestures for navigation
and the matrix is attached to the tablet in AR.
The selection of data items is shared across all scatterplots
within the matrix through linking and brushing.
In the next example we use a node-link diagram and attribute visualization
to demonstrate how to make relations between views visible.
We show an AR link with additional information between the two tablets.
Selections are again shared by linking and brushing.
Panning and zooming the node-link diagram allows us to filter the table.
In the third use case we show how an AR display extension can be used for map navigation.
Here, we realized different designs again:
On the left you can see a version showing all streets and objects;
On the right you see a more abstract version showing highways and water only.
Touch input on the tablet is used for navigation, data selection, and to access details-on-demand.
Tooltips move off-screen to AR when panning the map, which aims at assisting comparison of distant objects.
With a focus on spatio-temporal data, we also adapted a technique developed by Tominski and Schulz 2012.
A 3D wall visualization can be constructed by selecting several areas of interest.
Here, the wall encodes unemployment data over time, whereby the height represents time.
Interestingly, the tablet's tangibility literally fosters picking up and rotating the 3D visualization for inspection.
As another form of 3D visualization, we implemented 3D glyphs and trajectories aligned on a scatterplot.
The idea is to use AR to show the development of data attributes over time and thus provide a better overview.
As you can see, by selecting a data item on the tablet,
the development is displayed as a glyph or trajectory.
Glyphs are located right on top of an object and show the change of size over time.
Trajectories use the height above the tablet for an additional data dimension.
In the last use case we illustrate the concept of combining visualizations by using specific device arrangements.
Here, bar charts show the number of enrolled students for either different semesters or study courses.
The heatmap results from crossing these groups.
Selecting a bar on one of the tablets results in 3D stacked bars at the corresponding row or column.
These bars then show the proportions of enrolled students in terms of gender and country of origin.
In case of selections on both tablets,
bars at the intersection are visually highlighted by reducing the width of all other bars.
This was a quick overview of our work MARVIS, in which we explore an interesting device setup for data visualization:
Common mobile devices plus head-mounted Augmented Reality.
More details about our work and links to other videos
can be found on our project website imld.de/marvis.
Thank you for watching!