TY  - CHAP
AU  - Hoser, Bettina
AU  - Hotho, Andreas
AU  - Jäschke, Robert
AU  - Schmitz, Christoph
AU  - Stumme, Gerd
A2  - Sure, York
A2  - Domingue, John
T1  - Semantic Network Analysis of Ontologies
T2  - The Semantic Web: Research and Applications
PB  - Springer
CY  - Berlin/Heidelberg
PY  - 2006/
VL  - 4011
IS  - 
SP  - 514
EP  - 529
UR  - http://dx.doi.org/10.1007/11762256_38
M3  - 10.1007/11762256_38
KW  - 2006
KW  - iccs_example
KW  - l3s
KW  - myown
KW  - ontology
KW  - semantic
KW  - trias_example
KW  - sna
KW  - analysis
KW  - network
KW  - social
L1  - 
SN  - 978-3-540-34544-2
N1  - 
N1  - 
AB  -  A key argument for modeling knowledge in ontologies is the easy reuse and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA).While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies. We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size. 
ER  -