=Paper=
{{Paper
|id=Vol-2378/shortAT10
|storemode=property
|title=Toscana goes 3D: Using VR to Explore Life Tracks
|pdfUrl=https://ceur-ws.org/Vol-2378/shortAT10.pdf
|volume=Vol-2378
|authors=Christian Săcărea,Diana-Florina Şotropa,Raul-Robert Zavaczki
|dblpUrl=https://dblp.org/rec/conf/icfca/SacareaSZ19
}}
==Toscana goes 3D: Using VR to Explore Life Tracks==
https://ceur-ws.org/Vol-2378/shortAT10.pdf
Toscana goes 3D: Using VR to Explore Life
Tracks
Christian Săcărea, Diana-Florina Şotropa, and Raul-Robert Zavaczki
Babeş-Bolyai University Cluj-Napoca
csacarea@cs.ubbcluj.ro, diana.halita@ubbcluj.ro, zavaczki.raul@gmail.com
Abstract. Temporal Concept Analysis (TCA) has been developed with
the aim to investigate conceptual structures in data with a temporal
layer. Nevertheless, there are not so many tools enabling the visualization
of TCA features. We propose a new approach based on virtual reality
with a 3D representation of concept lattices in which life tracks of objects
can be displayed and explored. This is done by exporting the well-known
Toscana tool for visualizing conceptual landscapes in a virtual reality
(VR) environment and then display various TCA features on the selected
scales.
1 Introduction
Formal Concept Analysis (FCA) is well-known for its graphical Knowledge Rep-
resentation capabilities. There are a plethora of software tools which have been
developed over time, implementing various features. Over the last 30 years, al-
most all research groups have developed their own tools, an overview of which
is maintained by U. Priss1 . Nevertheless, there is no commercial software imple-
menting FCA methods, and, paradoxically, exactly those FCA varieties having
the most potential for real life applications are neglected: many-valued contexts
and temporal FCA. Many-valued contexts are handled by the ToscanaJ suite [1],
and an attempt to implement scaling features is done in FCA Tools Bundle2 [3].
Besides scale building (which is done using Elba), the ToscanaJ suite includes
also conceptual landscapes navigation capabilities, by defining a browsing sce-
nario and then perform navigation [5]. Unfortunately, ToscanaJ has not been
updated for a long time and there is a need to implement a more modern ver-
sion.
Even if K.E.Wolff, the founder of TCA [6] presented in several workshops
methods for using TCA in practice, a practical tool is missing. J. Poelmans [4]
presented a series of applications of TCA and he also developed software solu-
tions which, unfortunately, are not freely available. TCA has been developed to
deal with data having a clear temporal structure. However, there are surprisingly
Copyright c 2019 for this paper by its authors. Copying permitted for private and
academic purposes.
1
http://www.upriss.org.uk/fca/fcasoftware.html
2
fca-tools-bundle.com
2 C. Săcărea et al.
few real world examples of data sets which are analyzed using TCA. Of course,
the major reason is once more a missing software tool which is user friendly,
modern and appealing.
2 The project
With the development of new technologies and game engines3 , the modern
graphic capabilities of these technologies increased dramatically and it lies at
hand to try to use them in new FCA software. We present a prototype for 3D
visualization of concept lattices, conceptual landscapes as temporal FCA. We
also expect valuable feedback from the FCA community, as well as fruitful dis-
cussions on how modern technologies can be used in various software tools for
FCA and related fields.
Our research group4 started a project, called Toscana goes 3D in which we
use HTC VIVE VR headsets to visualize concept lattices, as well as conceptual
landscapes generated by Elba from the ToscanaJ suite. The target is to imple-
ment a new kind of Toscana visualizer. Even more, while investigating conceptual
structures in data with a temporal layer was previously studied, considering a
new approach based on virtual reality (VR) with a 3D representation of concept
lattices has not been studied yet. As a particular feature, we refer to the current
work in progress aiming to enhance Temporal Concept Analysis (TCA) with a
virtual reality perspective in order to study, display and explore life tracks of
objects.
Fig. 1: 3D concept lattice
3
https://unity3d.com/
4
cs.ubbcluj.ro/˜fca
Toscana goes 3D: Using VR to Explore Life Tracks 3
The technologies used are Unity3D, for a compatible working space that cur-
rently supports VR Headsets, meaning that it is a cross platform (and by thus
it supports HTC Vive, Oculus,etc.), and SteamVR 2D Plugin, the actual plugin
that helps us with VR I/O operations. The concept lattices are represented in
3D by using a circular cone like view of the nodes which are at the same depth
in the lattice. Concept lattices are computed with the NextClosure algorithm.
We have implemented a series of functionalities which include:
1. Navigating 3D concept lattices: Formal contexts in *.cxt format can be up-
loaded and we use the Next Closure algorithm for computing concept lattices.
Concept lattices are displayed in a VR 3D environment (for an example see
Figure 1) and we can move and rotate them (see below for a list of actions).
2. Navigating 3D conceptual landscapes: Once a conceptual schema (.csx file)
is created using Elba, the entire navigation process which is supported by
ToscanaJ for many-valued data sets is moved in the VR 3D environment.
3. By combining the effectiveness of conceptual scaling with virtual reality and
TCA we are able to automatize life tracks computation in the analyzed data
set and to display a timeline of events (Figure 2, [2]).
Fig. 2: 2D lifetrack in an e-learning environment
For moving nodes in the concept lattices or the entire concept lattice, you
have a couple of options:
– Point-and-action (Figure 3): you can select one or more nodes and move/rotate
them.
– Display a mini-lattice: A miniature lattice is shown, from where you can
drag one or more nodes to the desired position, the action is mimicked to
the original lattice.
Information display has also a couple of options:
4 C. Săcărea et al.
Fig. 3: Point and action
– Node information is shown in the corner as a box.
– Point-and-see: point at a node and the information is displayed nearby.
– And a couple more configurable options (see Figure 4: see the information
for selected nodes only/ see intents for all nodes/ see extents for all nodes.
Controls are user-friendly:
– Each hand has a mode selected: meaning that you can drag some nodes while
moving.
– Modes: Movement, Node, Lattice.
– Each mode have some sub-actions:
• Movement: Teleport, Fly
Fig. 4: Actions for a 3D concept lattice
• Node : Select, Select More (which operate similar to CTRL + Click on
an OS), Move, Rotate.
Toscana goes 3D: Using VR to Explore Life Tracks 5
• Lattice : Rotate, Scale.
– The trigger button - Triggers the action (teleport/rotate lattice )
– The touchpad click - Sub-action selection menu (Figure 5)
Fig. 5: Configurable selection menu
– The touchpad touch - Selecting a sub-action of the mode
– The grip click (also refered as grabbing ) - Selecting of mode
3 Conclusions
We invite researchers to test the tool and to make proposals for new function-
alities. The major aim of our research group5 is to develop a series of software
products which make the use of FCA tools more user friendly and appealing,
and by that to contribute to the popularization of FCA.
References
1. Becker, P., Correia, J.H.: The ToscanaJ Suite for Implementing Conceptual Informa-
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Foundations and Applications. LNCS, vol. 3626, pp. 324–348. Springer (2005)
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platforms using temporal concept analysis. In: ICFCA. Lecture Notes in Computer
Science, vol. 10308, pp. 122–137. Springer (2017)
3. Kis, L.L., Sacarea, C., Troanca, D.: FCA tools bundle - A tool that enables dyadic
and triadic conceptual navigation. In: Proceedings of the 5th International Work-
shop ”What can FCA do for Artificial Intelligence”? co-located with the European
Conference on Artificial Intelligence, FCA4AI@ECAI 2016, The Hague, the Nether-
lands, August 30, 2016. pp. 42–50 (2016)
4. Poelmans, J., Elzinga, P., Dedene, G., Viaene, S., Kuznetsov, S.O.: A concept dis-
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5. Wille, R.: Conceptual Landscapes of Knowledge: A Pragmatic Paradigm for Knowl-
edge Processing, pp. 344–356. Springer Berlin Heidelberg, Berlin, Heidelberg (1999)
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