Activities such as Web Services and the Semantic Web are working to create a web of distributed machine understandable data. In this paper we present an application called Semantic Search which is built on these supporting technologies and is designed to improve traditional web searching. We provide an overview of TAP, the application framework upon which the Semantic Search is built. We describe two implemented Semantic Search systems which, based on the denotation of the search query, augment traditional search results with relevant data aggregated from distributed sources. We also discuss some general issues related to searching and the Semantic Web and outline how an understanding of the semantics of the search terms can be used to provide better results.

Centralized Resource Description Framework (RDF) repositories have limitations both in their failure tolerance and in their scalability. Existing Peer-to-Peer (P2P) RDF repositories either cannot guarantee to find query results, even if these results exist in the network, or require up-front definition of RDF schemas and designation of super peers. We present a scalable distributed RDF repository ("RDFPeers") that stores each triple at three places in a multi-attribute addressable network by applying globally known hash functions to its subject, predicate, and object. Thus, all nodes know which node is responsible for storing triple values they are looking for, and both exact-match and range queries can be efficiently routed to those nodes. RDFPeers has no single point of failure nor elevated peers, and does not require the prior definition of RDF schemas. Queries are guaranteed to find matched triples in the network if the triples exist. In RDFPeers, both the number of neighbors per node and the number of routing hops for inserting RDF triples and for resolving most queries are logarithmic to the number of nodes in the network. We further performed experiments that show that the triple-storing load in RDFPeers differs by less than an order of magnitude between the most and the least loaded nodes for real-world RDF data.

SPARQL is the standard language for querying RDF data. In this article, we address systematically the formal study of the database aspects of SPARQL, concentrating in its graph pattern matching facility. We provide a compositional semantics for the core part of SPARQL, and study the complexity of the evaluation of several fragments of the language. Among other complexity results, we show that the evaluation of general SPARQL patterns is PSPACE-complete. We identify a large class of SPARQL patterns, defined by imposing a simple and natural syntactic restriction, where the query evaluation problem can be solved more efficiently. This restriction gives rise to the class of well-designed patterns. We show that the evaluation problem is coNP-complete for well-designed patterns. Moreover, we provide several rewriting rules for well-designed patterns whose application may have a considerable impact in the cost of evaluating SPARQL queries.

The Semantic Web is based on the idea of adding more machine-readable semantics to web information via annotations written in a language called the Resource Description Framework (RDF). RDF resembles a subset of binary first-order logic including the ability to refer to anonymous objects. Its extended version, RDFS, supports reification, typing and inheritance. These features introduce new challenges into the formal study of sets of RDF/RDFS statements and languages for querying them. Although several such query languages have been proposed, there has been little work on foundational aspects. We investigate these, including computational aspects of testing entailment and redundancy. We propose a query language with well-defined semantics and study the complexity of query processing, query containment, and simplification of answers.

Traditionally, research in applying Semantic Web technology to multimedia information systems has focused on using annotations and ontologies to improve the retrieval process. This paper concentrates on improving the presentation of the retrieval results.

Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In our view of Information Retrieval on the Semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, our approach includes an ontology-based scheme for the semiautomatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. Experiments are shown where our approach is tested on corpora of significant scale, showing clear improvements with respect to keyword-based search.

Generating hypermedia presentations requires processing constituent material into coherent, unified presentations. One large challenge is creating a generic process for producing hypermedia presentations from the semantics of potentially unfamiliar domains. The resulting presentations must both respect the underlying semantics and appear as coherent, plausible and, if possible, pleasant to the user. Among the related unsolved problems is the inclusion of discourse knowledge in the generation process. One potential approach is generating a discourse structure derived from generic processing of the underlying domain semantics, transforming this to a structured progression and then using this to steer the choice of hypermedia communicative devices used to convey the actual information in the resulting presentation.

Abstract. This paper presents an ontology-based approach for web querying, using semantic metadata. We propose a query language based on ontologies and emphasize its ability to express approximate queries, useful for an efficient information retrieval on the web. We present the Corese search engine dedicated to RDF(S) metadata and illustrate it through several real-world applications. 1

Abstract. This paper studies the RDF model from a database perspective. From this point of view it is compared with other database models, particularly with graph database models, which are very close in motivations and use cases to RDF. We concentrate on query languages, analyze current RDF trends, and propose the incorporation to RDF query languages of primitives which are not present today, based on the experience and techniques of graph database research. 1

Personalized access and content syndication involving diverse conceptual representations of information resources are two of the key challenges of real-scale Semantic Web (SW) applications, such as eCommerce, e-Learning or e-Science portals. RDF/S represents nowadays the core SW language for creating and exchanging resource descriptions worldwide. Unfortunately, full-fledged view definition languages for the RDF/S data model are still missing. We propose RVL, a view definition language capable of creating not only virtual resource descriptions, but also virtual RDF/S schemas from (meta)classes, properties, as well as, resource descriptions available on the Semantic Web. RVL exploits the functional nature and type system of the RQL query language in order to navigate, filter and restructure complex RDF/S schema and resource description graphs.