This is an archive of an inactive wiki and cannot be modified.

STAR:dust model: Semantic Travel Across Resources (STAR) with the aim of designing unified support tools (dust)

STAR:dust is a conceptual model aimed at designing and specifying the "travel" that web users undertake while surfing through resources. It provides a conceptualization that can be used as "application ontology" for model-driven software tools (called "vehicles") that support creation of pages, navigation and presentation of resources according to different views.

The STAR:dust model is made up of seven main primitives (Vehicle, Traveler, TravelType, HyperEnvironment, TravelModel, TravelObject and Mapping) and their relations. It is further divided into three sub-ontologies, partially defined ad hoc (e.g., most of the access model) and partially referring to shared and wide-spread models like SKOS and Dublin Core vocabulary: the navigation model, the access model and the presentation model.

Navigation model:
 * skos:related is used to define the connection between the current resource and other resources that are somehow similar or on the same subject;
 * skos:broader/skos:narrower are used to represent the connections between the current resource and those resources that are at a higher/lower level of complexity;
 * skos:relatedPartOf (part-of relation) represents the containment connection between the current resource and its parts (e.g., the relation between a section and its sub-sections);
 * skos:Concept is used to represent the "element", i.e. every "place" where it is possible to go and the portion of information that is relevant for the navigation. 
Access model:
 * axs:Home is the landmark indication, i.e. the denotation of specific resources that can be taken as reference for navigation;
 * axs:prev/axs:next relations are the connections between the current resource and those resources that are immediately before/after in a specific path;
 * axs:up/axs:down relations are the connections between the current resource and those resources that are immediately above/below in a specific ordered list or hierarchy.

The presentation model contains classes and properties to model all the characteristics of knowledge visualization, for example describing the different options (positioning, abbreviation) to visualize a long text in a page. It is composed of both existing primitives coming from popular and shared models (e.g., dc:title, dcterms:image or skos:symbol, skos:prefLabel and skos:altLabel) and building blocks modeled explicitly to represent e.g. the features useful for visualization functions (pres:hasText and its sub-properties pres:hasFullText, pres:hasShortText and pres:hasSlidebarText).

This STAR:dust model is represented in RDF/OWL:

The conceptual model specifies the "navigation and presentation semantics". The resulting vocabulary/ontology, however, is not useful per se, but it is used to strongly decouple the editing of contents from their visualization.

For example, it is assumed that the contents about a specific domain (e.g., artists and artwork of a museum) are edited by domain experts and provided/translated into a machine-readable format, namely OWL. Each portal has its own (multilingual) domain ontology, making use of hyperonymy/hyponymy, meronymy/holonymy (part-of relation), multiple wordings (homonymy/pseudonymy/synonymy) and generic semantic relationship whenever needed. Both limited and very huge ontologies (with millions of triples) have been experimented with.

Once we have this domain knowledge base, we can design a visualization by mapping between the domain ontology and the STAR:dust Travel model. For example, for a virtual museum portal, we map between the navigation/access/presentation models and the ontology of art and artists:

Generally, mappings actually match any kind of (sub)graph made with the domain ontology with any kind of graph made with components of the 3 STAR:dust models. For the simplest cases, SPARQL CONSTRUCT queries are used to perform those mappings.

Finally, a tool like SOIP-F (Semantic Organizational Information Portal framework,, taking as input both the domain knowledge and the mappings, makes lever on the STAR:dust model (including semantic descriptions of the users' profiles) and produce a way to present and navigate across contents.

Existing implementations (cf. feature semantic-based healthcare information portals (using respectively a medical ontology from the L&C TeSSI suite and PubMed bibliographic references with MeSH taxonomy), a virtual museum of contemporary art and a Semantic Web virtual lesson.