P. Mutton, and J. Golbeck. IEEE Int. Conf. on Information Visualization, London, IEEE, (2003)
Abstract
Implicit information embedded in semantic web graphs, such as topography, clusters, and disconnected subgraphs is difficult to extract from text files. Visualizations of the graphs can reveal some of these features, but existing systems for visualizing metadata focus on aspects other than understanding the greater structure. In this paper, we present a tool for generating visualizations of ontologies and metadata by using a modified spring embedder to achieve an automatic layout. Through a case study using a mid-sized ontology, we show that interesting information about the data relationships can be extracted through our visualization of the physical graph structure.
pretty interesting, OWL based spring layout of data models for exploring ontologies. steals a lot from SHriMP ideas interesting phrase"The spring embedded graph reveals several details about the general graph structure that are not clear from the CDM diagram. For example, one of the longest of these chains begins with Änimal" and ends with ÄnimalParentRelationshipBiologic". Again, it is intuitive that these two concepts should have some semantic relation, and through one intermediate concept and a simple string of subclasses, the two are chained together in the graph. However, the five steps separating the two concepts make it nearly impossible to recognize this relationship through text. Though tracing the path through the original CDM diagram is not difficult, there are no visual clues that would indicate it without close inspection." just like the NCI stuff!
%0 Conference Paper
%1 mutton03
%A Mutton, Paul
%A Golbeck, Jennifer
%B IEEE Int. Conf. on Information Visualization
%C London
%D 2003
%I IEEE
%K retrieval ontology information visualization
%T Visualization of Semantic Metadata and Ontologies
%U http://www.cs.toronto.edu/~nernst/papers/golbeck-iv03.pdf
%X Implicit information embedded in semantic web graphs, such as topography, clusters, and disconnected subgraphs is difficult to extract from text files. Visualizations of the graphs can reveal some of these features, but existing systems for visualizing metadata focus on aspects other than understanding the greater structure. In this paper, we present a tool for generating visualizations of ontologies and metadata by using a modified spring embedder to achieve an automatic layout. Through a case study using a mid-sized ontology, we show that interesting information about the data relationships can be extracted through our visualization of the physical graph structure.
@inproceedings{mutton03,
abstract = {Implicit information embedded in semantic web graphs, such as topography, clusters, and disconnected subgraphs is difficult to extract from text files. Visualizations of the graphs can reveal some of these features, but existing systems for visualizing metadata focus on aspects other than understanding the greater structure. In this paper, we present a tool for generating visualizations of ontologies and metadata by using a modified spring embedder to achieve an automatic layout. Through a case study using a mid-sized ontology, we show that interesting information about the data relationships can be extracted through our visualization of the physical graph structure.},
added-at = {2006-03-24T16:34:33.000+0100},
address = {London},
author = {Mutton, Paul and Golbeck, Jennifer},
biburl = {https://www.bibsonomy.org/bibtex/20ff4a40e0679eb2f928baa0688d7c55c/neilernst},
booktitle = {IEEE Int. Conf. on Information Visualization},
citeulike-article-id = {121811},
comment = {pretty interesting, OWL based spring layout of data models for exploring ontologies. steals a lot from SHriMP ideas interesting phrase"The spring embedded graph reveals several details about the general graph structure that are not clear from the CDM diagram. For example, one of the longest of these chains begins with "Animal" and ends with "AnimalParentRelationshipBiologic". Again, it is intuitive that these two concepts should have some semantic relation, and through one intermediate concept and a simple string of subclasses, the two are chained together in the graph. However, the five steps separating the two concepts make it nearly impossible to recognize this relationship through text. Though tracing the path through the original CDM diagram is not difficult, there are no visual clues that would indicate it without close inspection." just like the NCI stuff!},
description = {sdasda},
interhash = {278c1066ffb6900ce9853d31dbfbc6b5},
intrahash = {0ff4a40e0679eb2f928baa0688d7c55c},
keywords = {retrieval ontology information visualization},
priority = {0},
publisher = {IEEE},
timestamp = {2006-03-24T16:34:33.000+0100},
title = {Visualization of {S}emantic {M}etadata and {O}ntologies},
url = {http://www.cs.toronto.edu/~nernst/papers/golbeck-iv03.pdf},
year = 2003
}