StarLion: Auto-configurable
Layouts for
Exploring Ontologies
Stamatis Zampetakis, Yannis Tzitzikas,
Asterios Leonidis, and Dimitris Kotzinos
Institute of Computer Science, FORTH-ICS, Greece, and
Computer Science Department, University of Crete, Greece
Outline
Motivation
 StarLion

Exploration Method
Layout Algorithm
Ontology Dependencies

Conclusion
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Motivation

It is difficult to understand a big RDFS
ontology, even if it is visualized
(here as a labeled directed graph)
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 Exploration through Star Views

We propose exploring gradually the ontology
through StarViews
the user selects one class c as a focal point. Class c along with all
related classes in distance (radius) k from c are visualized
creating Star-like graphs
StarView on class Actor with radius 1
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Exploration through Star Graphs
Example
Cidoc CRM Ontology
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Exploration through Star Graphs
Example (cont)
StarView on E39 Actor with Radius = 1
Click on E30 Right
StarView On Class Actor with Radius 1
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Exploration through Star Graphs
Example (cont)
StarView on E30 Right with Radius = 1
StarView on Class Right with radius 1
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Exploration through Star Graphs
Example (cont): Increasing
the Radius
StarView on E30 Right with Radius = 2
StarView on Class Right with radius 2
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Exploration through Star Graphs
Example : Data Visualization

StarViews can also be used for data exploration
data usually come in big volumes which cannot be
visualized altogether
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How to layout these graphs?
Observations and Requirements
 Every graph has different features:
Different number of nodes, edges, isA (subclasssuperclass) relations

The layout algorithm that will be used, must be
configurable for adapting to every occasion
Our approach
 Adopt a force-directed placement algorithm
(FDPA) and focus on the configuration of its
parameters
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A force-directed placement
algorithm for RDFS
We view an RDF schema as a mechanical system
worksAt
Person
subClassOf
Manager
company
Person
company
subClassOf
Secretary
Manager
Magnet
ESWC'10 StarLion:Auto-configurable Layouts for Exploring Ontologies
Secretary
Magnetic
Field
Electrical
Repulsion
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A force-directed placement algorithm for RDFS >
Configuration

FDPA has three parameters that affect the produced
layout
Km – magnetic field strength
Ke – repulsion strength
L – spring length
 Our approach
• A toolbar for relative configuration
• A “Magic button”
• quality metrics and automatic configuration
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Configuring the Parameters
Toolbar for Relative Configuration
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Configuring the Parameters
The “Magic Button”

It measures the
quality of the layout
based on two metrics
Verticality of
specialization
hierarchies and
Layout area

Then it re-adjusts the
configuration
parameters for
improving the layout
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Configuring the Parameters
The “Magic Button”> Example

The layout with a simple application of the FDPA without any configuration
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Configuring the Parameters
The “Magic Button”> Example

After 1 application of the FDPA with automatic configuration
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Configuring the Parameters
The “Magic Button”> Example

After 2 applications of the FDPA with automatic configuration
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Visualization of Ontology
Dependencies
Ontologies usually extend other ontologies
In most cases visualizing parts of the related
ontologies is crucial for the understanding of the
main ontology
 Our Approach


We support three options for the visualization of an
ontology’s dependencies
Direct Dependencies: Main ontology + Only the directly
connected elements from the other related ontologies
Transitive Dependencies: Main ontology + Directly
connected elements from the other related ontologies
along with their superclasses
Full Dependencies: Visualize all related ontologies entirely
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Visualization of Dependent
Namespaces> Example
Cidoc CRM
Ontology
Extends
Cidoc CRM
Digital Ontology
Example:
Cidoc CRM Ditital Ontology extends
Cidoc CRM Ontology adding six new classes and a
few properties
By visualizing Cidoc CRM Digital Ontology
alone we get:
By visualizing Cidoc CRM Digital
Ontology taking into account its
dependency we get.
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Conclusion

In comparison with related works and systems:
Most of them do not support variable radius in
StarView
None of them uses a FDPA that takes into account
the subClassOf hierarchies
Most of them do not allow configuring the FDPA
parameters
They do not support auto-configuration of the FDPA
parameters
They do not exploit dependencies between
ontologies in the visualization
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THANKS FOR YOUR
ATTENTION
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