eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Dagstuhl Seminar Proceedings
1862-4405
2008-07-22
8191
1
10
10.4230/DagSemProc.08191.1
article
08191 Abstracts Collection – Graph Drawing with Applications to Bioinformatics and Social Sciences
Borgatti, Stephen
Kobourov, Stephen
Kohlbacher, Oliver
Mutzel, Petra
From May 4 to May 9, 2008, the Dagstuhl Seminar 08191 ``Graph Drawing with Applications to Bioinformatics and Social Sciences'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available.
https://drops.dagstuhl.de/storage/16dagstuhl-seminar-proceedings/dsp-vol08191/DagSemProc.08191.1/DagSemProc.08191.1.pdf
Graph drawing
visualization
social sciences
bioinformatics
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Dagstuhl Seminar Proceedings
1862-4405
2008-07-22
8191
1
3
10.4230/DagSemProc.08191.2
article
08191 Executive Summary – Graph Drawing with Applications to Bioinformatics and Social Sciences
Borgatti, Stephen
Kobourov, Stephen
Kohlbacher, Oliver
Mutzel, Petra
Graph drawing deals with the problem of communicating the structure of
relational data through diagrams, or drawings. The ability to represent
relational information in a graphical form is a powerful tool which allows
to perform analysis through visual exploration to find important patterns,
trends, and correlations. Real-world applications such as bioinformatics and
sociology pose challenges to the relational visualization because, e.g., semantic
information carried by the diagram has to be used for obtaining meaningful layouts and
application-specific drawing conventions need to be fulfilled. Moreover, the
underlying data often stems from huge data bases, but only a small fraction
shall be displayed at a time; the user interactively selects the data to be
displayed and explores the graph by expanding interesting and collapsing
irrelevant parts. This requires powerful graph exploration tools with
navigation capabilities that allow dynamic adaption of the graph layout in real
time. In this seminar we focused on the application of graph drawing in two
important application domains: bioinformatics and social sciences.
We brought together theoreticians and practitioners from these areas
and focused on problems concerning interaction with and navigation in large
and dynamic networks arising in these application areas;
During the seminar, we identified and defined open graph drawing problems
that are motivated by practical applications in the targeted application areas,
tackled selected open problems, formulated the findings as a first step to
the solution, and defined further research directions.
https://drops.dagstuhl.de/storage/16dagstuhl-seminar-proceedings/dsp-vol08191/DagSemProc.08191.2/DagSemProc.08191.2.pdf
Graph drawing
visualization
social sciences
bioinformatics
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Dagstuhl Seminar Proceedings
1862-4405
2008-07-22
8191
1
3
10.4230/DagSemProc.08191.3
article
08191 Working Group Report – Edge Thresholding
Healy, Patrick
Dwyer, Tim
When working with very large networks it is
typical for scientists to present a ``thinned out'' version of the
network in order to avoid the clutter of the entire network. For
example in the hypothetical case of illustrating trading patterns
between groups of nations it might be appropriate to limit the inclusion
of inter-nation edges to all those that are significant in terms of
their weight but do not, say, associate with a country outside the
grouping. Arising from a discussion during one of the introductory
sessions we became interested in a problem relating to the discovery of
``key events'' in a network, in terms of an ordered addition of edges to
the network.
https://drops.dagstuhl.de/storage/16dagstuhl-seminar-proceedings/dsp-vol08191/DagSemProc.08191.3/DagSemProc.08191.3.pdf
Graph drawing
edge thresholding
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Dagstuhl Seminar Proceedings
1862-4405
2008-07-22
8191
1
3
10.4230/DagSemProc.08191.4
article
08191 Working Group Report – Visualization of Trajectories
Borgatti, Stephen
Brandes, Ulrik
Kaufmann, Michael
Kobourov, Stephen
Lubiw, Anna
Wagner, Dorothea
We considered the following problem: Given a set of vertices V and a set of paths
P, where each path is a sequence of vertices, represent these paths somehow.
We explored representations in different dimensions and with different conditions on the paths.
https://drops.dagstuhl.de/storage/16dagstuhl-seminar-proceedings/dsp-vol08191/DagSemProc.08191.4/DagSemProc.08191.4.pdf
Graph drawing
trajectories
paths
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Dagstuhl Seminar Proceedings
1862-4405
2008-07-22
8191
1
17
10.4230/DagSemProc.08191.5
article
08191 Working Group Report – X-graphs of Y-graphs and their Representations
Batagelj, Vladimir
Brandenburg, Franz J.
Didimo, Walter
Liotta, Guiseppe
Patrignani, Maurizio
We address graph decomposition problems that help the hybrid visualization of large
graphs, where different graphic metaphors (node-link, matrix, etc.) are used in the same
picture. We generalize the $X$-graphs of $Y$-graphs model introduced by Brandenburg
(Brandenburg, F.J.: Graph clustering I: Cycles of cliques. In Di Battista, G.,
ed.: Graph Drawing (Proc. GD '97). Volume 1353 of Lecture Notes Comput. Sci., Springer-Verlag
(1997) 158--168) to formalize the problem of automatically identifying dense subgraphs
($Y$-graphs, clusters) that are prone to be collapsed and shown with a matricial
representation when needed. We show that (planar, $K_5$)-recognition, that is, the
problem of identifying $K_5$ subgraphs such that the graph obtained by collapsing them
is planar, is NP-hard. On the positive side, we show that it is possible to determine the
highest value of $k$ such that $G$ is a (planar,$k$-core)-graph in $O(m + n log(n))$ time.
https://drops.dagstuhl.de/storage/16dagstuhl-seminar-proceedings/dsp-vol08191/DagSemProc.08191.5/DagSemProc.08191.5.pdf
Graph drawing
X-graphs of Y-graphs
visualization of large graphs
eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Dagstuhl Seminar Proceedings
1862-4405
2008-07-22
8191
1
6
10.4230/DagSemProc.08191.6
article
08191 Working Group Summary – Visually Comparing a Set of Graphs
Albrecht, Mario
Estrella-Balderrama, Alejandro
Geyer, Markus
Gutwenger, Carsten
Klein, Karsten
Kohlbacher, Oliver
Schulz, Michael
We consider methods to visually compare graphs, more to focus
on the differences of the graphs than on the similarities. Our two-level
approach constructs a meaningful overview of the given graphs combined with a
detailed view focusing on a local area of change.
The actual layout of these graphs has to be evaluated depending on the specific
type of biological network to be visualized in each case. We look into different
variants and propose properties to be optimized in our visualizations.
https://drops.dagstuhl.de/storage/16dagstuhl-seminar-proceedings/dsp-vol08191/DagSemProc.08191.6/DagSemProc.08191.6.pdf
Graph drawing
visual graph comparison