TY - GEN
T1 - Visual summaries for graph collections
AU - Koop, David
AU - Freire, Juliana
AU - Silva, Claudio
PY - 2013
Y1 - 2013
N2 - Graphs can be used to represent a variety of information, from molecular structures to biological pathways to computational workflows. With a growing volume of data represented as graphs, the problem of understanding and analyzing the variations in a collection of graphs is of increasing importance. We present an algorithm to compute a single summary graph that efficiently encodes an entire collection of graphs by finding and merging similar nodes and edges. Instead of only merging nodes and edges that are exactly the same, we use domain-specific comparison functions to collapse similar nodes and edges which allows us to generate more compact representations of the collection. In addition, we have developed methods that allow users to interactively control the display of these summary graphs. These interactions include the ability to highlight individual graphs in the summary, control the succinctness of the summary, and explicitly define when specific nodes should or should not be merged. We show that our approach to generating and interacting with graph summaries leads to a better understanding of a graph collection by allowing users to more easily identify common substructures and key differences between graphs.
AB - Graphs can be used to represent a variety of information, from molecular structures to biological pathways to computational workflows. With a growing volume of data represented as graphs, the problem of understanding and analyzing the variations in a collection of graphs is of increasing importance. We present an algorithm to compute a single summary graph that efficiently encodes an entire collection of graphs by finding and merging similar nodes and edges. Instead of only merging nodes and edges that are exactly the same, we use domain-specific comparison functions to collapse similar nodes and edges which allows us to generate more compact representations of the collection. In addition, we have developed methods that allow users to interactively control the display of these summary graphs. These interactions include the ability to highlight individual graphs in the summary, control the succinctness of the summary, and explicitly define when specific nodes should or should not be merged. We show that our approach to generating and interacting with graph summaries leads to a better understanding of a graph collection by allowing users to more easily identify common substructures and key differences between graphs.
UR - http://www.scopus.com/inward/record.url?scp=84888988567&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84888988567&partnerID=8YFLogxK
U2 - 10.1109/PacificVis.2013.6596128
DO - 10.1109/PacificVis.2013.6596128
M3 - Conference contribution
AN - SCOPUS:84888988567
SN - 9781467347976
T3 - IEEE Pacific Visualization Symposium
SP - 57
EP - 64
BT - IEEE Symposium on Pacific Visualization 2013, PacificVis 2013 - Proceedings
T2 - 6th IEEE Symposium on Pacific Visualization, PacificVis 2013
Y2 - 26 February 2013 through 1 March 2013
ER -