Winnowing ontologies based on application use

The requirements of specific applications and services are often over estimated when ontologies are reused or built. This sometimes results in many ontologies being too large for their intended purposes. It is not uncommon that when applications and services are deployed over an ontology, only a few parts of the ontology are queried and used. Identifying which parts of an ontology are being used could be helpful to winnow the ontology, i.e., simplify or shrink the ontology to smaller, more fit for purpose size. Some approaches to handle this problem have already been suggested in the literature. However, none of that work showed how ontology-based applications can be used in the ontology-resizing process, or how they might be affected by it. This paper presents a study on the use of the AKT Reference Ontology by a number of applications and services,and investigates the possibility of relying on this usage information to winnow that ontology

RDFSculpt: Managing RDF schemas under set-like semantics

Abstract. The Semantic Web is an extension of the current Web in which information is given well-defined meaning to support effective data discovery and integration. The RDF framework is a key issue for the Se-mantic Web. It can be used in resource discovery to provide better search engine capabilities, in cataloging for describing the content of thematic hierarchies in thematic catalogs and digital libraries, in knowledge shar-ing and exchange of Web agents, etc. Up to now, RDF schemas have been treated rather as sets of individual elements (i.e. model primitives like classes, properties, etc.). Under that view, queries like “find the part of a portal catalog which is not present in another catalog ” can be answered only in a procedural way, specifying which nodes to select and how to get them. For this reason, we argue that answering such queries requires treating schemas as a whole rather than as sets of individual elements. We introduce a set of operators with set-like semantics to manage RDF schemas. The operators can be included in any RDF query language to support manipulation of RDF schemas as full-fledged objects. We also present RDFSculpt, a prototype system that implements our framework.

Viewing the Semantic Web Through RVL Lenses

Personalized access and content syndication involving diverse conceptual representations of information resources are two of the key challenges of Semantic Web applications. In this paper, we investigate how these goals can be achieved using view definition primitives over RDF/S bases. We introduce a full-fledged view definition language, RVL, for creating virtual RDF/S resource descriptions and schemas from (meta)classes, properties, and resource descriptions and we illustrate how RVL views can be composed with structured RDF/S queries expressed in a query language like RQL, by means of an internal logical framework capturing the semantics of the RDF/S model, RQL queries and RVL views. Key words: semantic web, query languages, views

Benchmarking Database Representations of RDF/S Stores

In this paper we benchmark three popular database representations of RDF/S schemata and data: (a) a schema-aware (i.e., one table per RDF/S class or property) with explicit (ISA) or implicit (NOISA) storage of subsumption relationships, (b) a schema-oblivious (i.e., a single table with triples of the form 〈subject-predicate-object〉), using (ID) or not (URI) identifiers to represent resources and (c) a hybrid of the schema-aware and schema-oblivious representations (i.e., one table per RDF/S meta-class by distinguishing also the range type of properties). Furthermore, we benchmark two common approaches for evaluating taxonomic queries either on-the-fly (ISA, NOISA, Hybrid), or by precomputing the transitive closure of subsumption relationships (MatView, URI, ID). The main conclusion drawn from our experiments is that the evaluation of taxonomic queries is most efficient over RDF/S stores utilizing the Hybrid and MatView representations. Of the rest, schema-aware representations (ISA, NOISA) exhibit overall better performance than URI, which is superior to that of ID, which exhibits the overall worst performance

A Survey of the Web Ontology Landscape

Abstract. We survey nearly 1300 OWL ontologies and RDFS schemas. The collection of statistical data allows us to perform analysis and report some trends. Though most of the documents are syntactically OWL Full, very few stay in OWL Full when they are syntactically patched by adding type triples. We also report the frequency of occurrences of OWL language constructs and the shape of class hierarchies in the ontologies. Finally, we note that of the largest ontologies surveyed here, most do not exceed the description logic expressivity of ALC.

RUL: A Declarative Update Language for RDF

We propose a declarative update language for RDF graphs which is based on the paradigms of query and view languages RQL and RVL. Our language, called RUL, ensures that the execution of the update primitives on nodes and arcs neither violates the semantics of the RDF model nor the semantics of the given RDFS schema. In addition, RUL supports fine-grained updates at the class and property instance level, set-oriented updates with a deterministic semantics and takes benefit of the full expressive power of RQL for restricting the range of variables to nodes and arcs of RDF graphs

Characterizing the Semantic Web on the Web

Abstract. Semantic Web languages are being used to represent, encode and exchange semantic data in many contexts beyond the Web – in databases, multiagent systems, mobile computing, and ad hoc networking environments. The core paradigm, however, remains what we call the Web aspect of the Semantic Web – its use by independent and distributed agents who publish and consume data on the World Wide Web. To better understand this central use case, we have harvested and analyzed a collection of Semantic Web documents from an estimated ten million available on the Web. Using a corpus of more than 1.7 million documents comprising over 300 million RDF triples, we describe a number of global metrics, properties and usage patterns. Most of the metrics, such as the size of Semantic Web documents and the use frequency of Semantic Web terms, were found to follow a power law distribution.