Haylyn - Collaborative 3D Semantic Web Visualization and Analytics (Formerly Nexus)

Haylyn is an experimental collaborative 3D Semantic Web visualization tool being built with (WebGL/OpenSimulator) to test various ideas and design concepts in visualizations, software design, and algorithms.

Some key paradigms and principals are being following in Haylyn's design:
1) Must be collaborative - all visualizations must be sharable in real-time accross multiple clients regardless of location.
2) All-RDF - rather than use any custom formats or internal data representations, RDF is used throughout Haylyn's architecture.  Haylyn consumes, internalizes, and exports everythying as RDF - Client/server communications are in RDF, user and client sessions are in RDF, cursor postion and directional vectors are in RDF, even the visualizations themselves are in RDF which allows them to be tightly coupled with the original data itself.
3) Explore 3D - many graph layout programs use 2D layout but 3D is being explored in Haylyn including 4D (time-based)
4) If a best-practice dogma is encountered, I follow this quote:

“Do not go where the path may lead, go instead where there is no path and leave a trail.”
Ralph Waldo Emerson

Molecular visualization is achievable in Haylyn because of it's ontology-driven visualization model.  The added benefit in doing it this way is that other semantic data sources can be linked and referenced while searching for/or working with a particular structure(s).  In addition, since Haylyn is driven by a SPARQL query engine (Jena ARQ), molecular selection criteria become more flexible by allowing a SPARQL query to be used to pick which parts of a structure are acted upon for display or modification.  Haylyn is not limited to just molecular visualization but will be able to visualize various semantic datatypes (FOAF, DOAC, etc) from multiple data sources.