Visualisation of Ontologies and Large Scale Graphs

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For a whole number of reasons, I am currently looking into the visualisation of large-scale graphs and ontologies and to that end, I have made some notes concerning tools and concepts which might be useful for others. Here they are:

Visualisation by Node-Link and Tree

jOWL: jQuery Plugin for the navigation and visualisation of OWL ontologies and RDFS documents. Visualisations mainly as trees, navigation bars.

OntoViz: Plugin into Protege…at the moment supports Protege 3.4 and doesn’t seem to work with Protege 4.

IsaViz: Much the same as OntoViz really. Last stable version 2004 and does not seem to see active development.

NeOn Toolkit: The Neon toolkit also has some visualisation capability, but not independent of the editor. Under active development with a growing user base.

OntoTrack: OntoTrack is a graphical OWL editor and as such has visualisation capabilities. Meager though and it does not seem to be supported or developed anymore either…the current version seems about 5 years old.

Cone Trees: Cone trees are three-dimensional extensions of 2D tree structures and have been designed to allow for a greater amount odf information to be visualised and navigated. Not found any software for download at the moment, but the idea is so interesting that we should bear it in mind. Examples are here, here and the key reference is Robertson, George G. and Mackinlay, Jock D. and Card, Stuart K., Cone Trees: animated 3D visualizations of hierarchical information, CHI ’91: Proceedings of the SIGCHI conference on Human factors in computing systems, 1991, ISBN = 0-89791-383-3, pp.189-194. (DOI here)

PhyloWidget: PhyloWidget is software for the visualisation of phylogenetic trees, but should be repurposable for ontology trees. Javascript – so appropriate for websites. Student project as part of the Phyloinformatics Summer of Code 2007.

The JavaScript Information Visualization Toolkit: Extremely pretty JS toolkit for the visualisation of graphs etc…..Dynamic and interactive visualisations too…just pretty. Have spent some time hacking with it and I am becoming a fan.

Welkin: Standalone application for the visualisation of RDF graphs. Allows dynamic filtering, colour coding of resources etc…

Three-Dimensional Visualisation

Ontosphere3D: Visualisation of ontologies on 3D spheres. Does not seem to be supported anymore and requires Java 3D, which is just a bad nightmare in itself.

Cone Trees (see above) with their extension of Disc Trees (for an example of disc trees, see here

3D Hyperbolic Tree as exemplified by the Walrus software. Originally developed for website visualisation, results in stunnign images. Not under active development anymore, but source code available for download.

Cytoscape: The 1000 pound gorilla in the room of large-scale graph visualization. There are several plugins available for interaction with the Gene Ontology, such as BiNGO and ClueGO. Both tools consider the ontologies as annotation rather than a knowledgebase of its own and can be used for the identification of GO terms, which are overrepresented in a cluster/network. In terms of visualisation of ontologies themselves, there is there is the RDFScape plugin, which can visualize ontologies.

Zoomable Visualisations

Jamabalaya – Protege Plugin, but can also run as a browser applet. Uses Shrimp to visualise class hierarchies in ontologies and arrows between boxes to represent relationships.

CropCircles (link is to the paper describing it): CropCircles have been implemented in the SWOOP ontology editor which is not under active development anymore, but where the source code is available.

Information Landscapes – again, no software, just papers.

SWAT4LS2009 – Michael Schroeder: Predicton of Drug Target Interactions from Literature by Context Similarity

Typical researcher spends 12.4 hours a week searching for information. Why not use Google? ‘Cause Google is not semantic.

Go PubMed – Filter PubMed contents against all the terms in the Gene Ontology. If you use simple categorisation for information retrieval potentially increase search burden due to compartmentalisation. However works the other way round too…useful filtering.

Showing some examples of faceted browsing of PubMed content and systematic drilldown into search results. Not easy to blog, but literature exploration in this way is always fascinating. Examples include the analysis of research trends, networks of colaborators etc..new tool in Go PubMed also allows the discovery of indirect links or inferred links.

Have developed a similar system for the web: Go Web (works on the top yahoo search results).

Remarks on Ontology Generation: have developed a plugin for OBO Edit…search for term and plugin makes suggestions for terms that might be included in new ontologies. Points out terms in existing ontologies. Also helps with the generation of definitions for terms…wow this is extremely useful in SO many ways….

Now let’s talk about drugs and targets….

Try and mine for gene mentions in text…find a gene term and then use context to decide what it is we are talking about. Once gene has found look for statistically significant co-occurences. The results have been made available in GoGene. Again can do bibliometric trend analysis – genes are ranked by community interest.

From drugs to genes..what is the link between a gene and a drug using context profiles: what are the disease terms related to a given drug…then to genes.

Gotta stop blogging…enjoying this talk far too much…….