The Semantic Web consists of many RDF graphs nameable by URIs. This paper

Abstract. A web of linked RDF data may be enabled by standards specifying how links should be made in RDF and under what conditions they should be followed as well as powerful generic RDF browsers that can traverse an open web of RDF resources. The Tabulator is an RDF browser, which is designed both for new users to provoke interest in the Semantic Web and give them a means to access and interact with the entire web of RDF data, and for developers of RDF content to provide incentive for them to post their data in RDF, to refine and promote RDF linking standards, and to let providers see how their data interacts with the rest of the Semantic Web. A challenge for Semantic Web browsers is to bring the power of domain-specific applications to a generic program when new unexpected domains can be encountered in real time. The Tabulator project is an attempt to demonstrate and utilize the power of linked RDF data with a user-friendly Semantic Web browser that is able to recognize and follow RDF links to other RDF resources based on the user’s exploration and analysis. 1

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.

Abstract. Semantic Web browsers and other tools aimed at displaying RDF data to end users are all concerned with the same problem: presenting content primarily intended for machine consumption in a human-readable way. Their solutions differ but in the end address the same two high-level issues, no matter the underlying representation paradigm: specifying (i) what information contained in RDF models should be presented (content selection) and (ii) how this information should be presented (content formatting and styling). However, each tool currently relies on its own ad hoc mechanisms and vocabulary for specifying RDF presentation knowledge, making it difficult to share and reuse such knowledge across applications. Recognizing the general need for presenting RDF content to users and wanting to promote the exchange of presentation knowledge, we designed Fresnel as a browser-independent vocabulary of core RDF display concepts. In this paper we describe Fresnel’s main concepts and present several RDF browsers and visualization tools that have adopted the vocabulary so far. 1

database systems

Abstract. Discovery of semantic associations in Semantic Web ontologies is an important task in various analytical activities. Several query languages and storage systems have been designed and implemented for storage and retrieval of information in RDF ontologies. However, they are inadequate for semantic association discovery. In this paper we present the design and implementation of BRAHMS, an efficient RDF storage system, specifically designed to support fast semantic association discovery in large RDF bases. We present memory usage and timing results of several tests performed with BRAHMS and compare them to similar tests performed using Jena, Sesame, and Redland, three of the well-known RDF storage systems. Our results show that BRAHMS handles basic association discovery well, while the RDF query languages and even the low-level APIs in the other three tested systems are not suitable for the implementation of semantic association discovery algorithms. 1

Abstract. The casual user is typically overwhelmed by the formal logic of the Semantic Web. The gap between the end user and the logic-based scaffolding has to be bridged if the Semantic Web’s capabilities are to be utilized by the general public. This paper proposes that controlled natural languages offer one way to bridge the gap. We introduce GINO, a guided input natural language ontology editor that allows users to edit and query ontologies in a language akin to English. It uses a small static grammar, which it dynamically extends with elements from the loaded ontologies. The usability evaluation shows that GINO is well-suited for novice users when editing ontologies. We believe that the use of guided entry overcomes the habitability problem, which adversely affects most natural language systems. Additionally, the approach’s dynamic grammar generation allows for easy adaptation to new ontologies. 1

Abstract. Complex relationships, frequently referred to as semantic associations, are the essence of the Semantic Web. Query and retrieval of semantic associations has been an important task in many analytical and scientific activities, such as detecting money laundering and querying for metabolic pathways in biochemistry. We believe that support for semantic path queries should be an integral component of RDF query languages. In this paper, we present SPARQLeR, a novel extension of the SPARQL query language which adds the support for semantic path queries. The proposed extension fits seamlessly within the overall syntax and semantics of SPARQL and allows easy and natural formulation of queries involving a wide variety of regular path patterns in RDF graphs. SPARQLeR's path patterns can capture many low-level details of the queried associations. We also present an implementation of SPARQLeR and its initial performance results. Our implementation is built over BRAHMS, our own RDF storage system. 1

Abstract. This paper studies the expressive power of SPARQL. The main result is that SPARQL and non-recursive safe Datalog with negation have equivalent expressive power, and hence, by classical results, SPARQL is equivalent from an expressive point of view to Relational Algebra. We present explicit generic rules of the transformations in both directions. Among other findings of the paper are the proof that negation can be simulated in SPARQL, that non-safe filters are superfluous, and that current SPARQL W3C semantics can be simplified to a standard compositional one. 1

Abstract. The Web of Linked Data forms a single, globally distributed dataspace. Due to the openness of this dataspace, it is not possible to know in advance all data sources that might be relevant for query answering. This openness poses a new challenge that is not addressed by traditional research on federated query processing. In this paper we present an approach to execute SPARQL queries over the Web of Linked Data. The main idea of our approach is to discover data that might be relevant for answering a query during the query execution itself. This discovery is driven by following RDF links between data sources based on URIs in the query and in partial results. The URIs are resolved over the HTTP protocol into RDF data which is continuously added to the queried dataset. This paper describes concepts and algorithms to implement our approach using an iterator-based pipeline. We introduce a formalization of the pipelining approach and show that classical iterators may cause blocking due to the latency of HTTP requests. To avoid blocking, we propose an extension of the iterator paradigm. The evaluation of our approach shows its strengths as well as the still existing challenges. 1