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The STAR:dust conceptual model: Semantic Travel Across Resources (STAR) with the aim of designing unified support tools (dust) to help travelers in their navigation

Contact e-mail: irene.celino # (main contact)

emanuele.dellavalle #

francesco.corcoglioniti #


General purpose and services to the end user

STAR:dust is a conceptual model aimed at designing and specifying the navigation, i.e. the "travel" that web users undertake while surfing through resources. It provides a thorough conceptualization that can be used as "application ontology" (in a Model-driven Architecture approach) for software tools (called "vehicles" in the metaphor of travel) that support the navigation and the presentation of resources.

Functionality examples

The STAR:dust model is used to design:

For example, in the presentation model, we describe the different options to visualize a long text: the text could be displayed in full at the center of the page; or it could be abbreviated (the first few words followed by dots) leaving the rest of the text "behind" a hyperlink or a button; finally, it could be inserted in a box or frame with scrollbars, in order to present all the details without taking up too much space.

Application architecture

The STAR:dust 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, we assume 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. Once we have this domain knowledge base, we can design their visualization by mapping between the domain ontology and the STAR:dust Travel model.

Finally, a tool like SOIP-F (, taking as input both the domain knowledge and the mappings, makes lever on the STAR:dust model and produce a way to present and navigate across contents.

Special strategies involved in the processing of user actions

The links and pages generation are based on the mappings between the travel model and the domain-specific ontology; moreover, this can be enhanced by exploiting the semantic descriptions of the users' profiles and preferences.

Integration between vocabulary-linked functions and other application functions

We designed the STAR:dust model with the aim of enabling the implementation of model-driven applications that takes STAR:dust as "application ontology" (see SOIP-F at; this approach makes the application capable to generate the pages starting from the model.

Additional references

SOIP-F (Semantic Organizational Information Portal framework) is a framework for building portals enhanced by semantics. Several domain specific portals were built on top of SOIP-F and are available on-line and listed on the web at Some publications about STAR:dust and SOIP-F are available on the web at



The top-level vocabulary is the STAR:dust conceptual model. The Travel model is the main vocabulary that is made up of three parts: the navigation model, the access model and the presentation model.

General characteristics (size, coverage) of the vocabulary

The STAR:dust model is made up of the main seven primitives (Vehicle, Traveler, TravelType, HyperEnvironment, TravelModel, TravelObject and Mapping) and their relations. The three parts of the Travel model are three 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.

However, each application based on STAR:dust will define and exploit mappings between the Travel model and the domain-specific ontologies. In our running applications, each portals has its own ontology and we experimented both limited and very huge ontologies (with millions of triples). Domain ontologies make use of hyperonymy/hyponymy, meronymy/holonymy (part-of relation), multiple wordings (homonymy/pseudonymy/synonymy) and generic semantic relationship whenever needed.

Language(s) in which the vocabulary is provided

STAR:dust and the Travel model are not multilingual, since they are used by the software (and they don't have to be visualized to the users). The domain-specific ontologies however can have labels in multiple languages to allow the display of information in the language of the user.

Vocabulary extract

Navigation model:

Access model:

Presentation model:

It contains a lot of classes and properties to model all the characteristics of knowledge visualization. The resulting ontology is composed of both existing primitives coming from popular and shared models (e.g., properties like dc:title, dcterms:image or skos:symbol, skos:prefLabel and skos:altLabel) and other building blocks we modeled explicitly to represent e.g. the features useful for visualization functions mentioned in section 1 (pres:hasText and its sub-properties pres:hasFullText, pres:hasShortText and pres:hasSlidebarText)

Machine-readable representation of the vocabulary

The Travel model is modeled in RDF/OWL and all the domain ontologies used in running applications were also expressed in RDF/OWL.

Some sample triples from the access ontology of the Travel model:

Software applications used to create and/or maintain the vocabulary, features lacking for the case

The vocabulary maintenance is performed through an RDF/SKOS/OWL editor.

Structure of the database used to currently manage the vocabulary

We use Sesame repositories with a MySQL backend to store the knowledge bases in RDF format using Sesame pre-defined structures (therefore we didn't need to define any table structure).

Standards and guidelines considered during the design and construction of the vocabulary

Generally, we use Methontology ( to build OWL ontologies. In the modeling of our SKOS-based ontologies, we made also use of the "Quick Guide to Publishing a Thesaurus on the Semantic Web" ( and the "SKOS Core Guide" (

Management of changes

The vocabulary maintenance is performed manually.

Additional references

Some publications about STAR:dust and SOIP-F are available on the web at

Some SOIP-F implementations are (cf.

Vocabulary mappings

Mapped vocabularies

We use a mapping approach to put in relation the Travel model with the domain-specific ontology to build the single domain specific application. For example, in the virtual museum portal, we map between the navigation/access/presentation models and the ontology of art and artists.

Extracts of Mappings

We give hereafter some simple examples for the Virtual Museum portal.

Types of mapping used

We use different kinds of mapping between the Travel model and the domain ontology. 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.

Additional references

See for more information. Details about SOIP-F can be also found in some publications about its implementation, available on-line at