Abstract. Swoogle helps software agents and knowledge engineers find Semantic Web knowledge encoded in RDF and OWL documents on the Web. Navigating such a Semantic Web on the Web is difficult due to the paucity of explicit hyperlinks beyond the namespaces in URIrefs and the few inter-document links like rdfs:seeAlso and owl:imports. In order to solve this issue, this paper proposes a novel Semantic Web navigation model providing additional navigation paths through Swoogle’s search services such as the Ontology Dictionary. Using this model, we have developed algorithms for ranking the importance of Semantic Web objects at three levels of granularity: documents, terms and RDF graphs. Experiments show that Swoogle outperforms conventional web search engine and other ontology libraries in finding more ontologies, ranking their importance, and thus promoting the use and emergence of consensus ontologies. 1

The openness of the Web and the ease to combine linked data from different sources creates new challenges. Systems that consume linked data must evaluate quality and trustworthiness of the data. A common approach for data quality assessment is the analysis of provenance information. For this reason, this paper discusses provenance of data on the Web and proposes a suitable provenance model. While traditional provenance research usually addresses the creation of data, our provenance model also represents data access, a dimension of provenance that is particularly relevant in the context of Web data. Based on our model we identify options to obtain provenance information and we raise open questions concerning the publication of provenance-related metadata for linked data on the Web.

Abstract. The World Wide Web evolves into a Web of Data, a huge, globally distributed dataspace that contains a rich body of machineprocessable information from a virtually unbound set of providers covering a wide range of topics. However, due to the openness of the Web little is known about who created the data and how. The fact that a large amount of the data on the Web is derived by replication, query processing, modification, or merging raises concerns of information quality. Poor quality data may propagate quickly and contaminate the Web of Data. Provenance information about who created and published the data and how, provides the means for quality assessment. This paper takes a first step towards creating a quality-aware Web of Data: we present approaches to integrate provenance information into the Web of Data and we illustrate how this information can be consumed. In particular, we introduce a vocabulary to describe provenance of Web data as metadata and we discuss possibilities to make such provenance metadata accessible as part of the Web of Data. Furthermore, we describe how this metadata can be queried and consumed to identify outdated information. 1

The Semantic Web provides a way to encode information and knowledge on web pages in a form that is easier for computers to understand and process. This article discusses the issues underlying the discovery, indexing and search over web documents that contain semantic web markup. Unlike conventional Web search engines, which use information retrieval techniques designed for documents of unstructured text, Semantic Web search engines must handle documents comprised of semi-structured data. Moreover, the meaning of data is defined by associated ontologies that are also encoded as semantic web documents whose processing may require significant amount of reasoning. We describe Swoogle, an implemented semantic web search engine that discovers, analyzes, and indexes knowledge encoded in semantic web documents throughout the Web, and illustrate its use to help human users and software agents find relevant knowledge. 1

Semantic inferencing and querying across largescale RDF triple stores is notoriously slow. Our objective is to expedite this process by employing Google’s MapReduce framework to implement scale-out distributed querying and reasoning. This approach requires RDF graphs to be decomposed into smaller units that are distributed across computational nodes. RDF Molecules appear to offer an ideal approach – providing an intermediate level of granularity between RDF graphs and triples. However, the original RDF molecule definition has inherent limitations that will adversely affect performance. In this paper, we propose a number of extensions to RDF molecules (hierarchy and ordering) to overcome these limitations. We then present some implementation details for our MapReduce-based RDF molecule store. Finally we evaluate the benefits of our approach in the context of the Bio-MANTA project – an application that requires integration and querying across large-scale protein-protein interaction datasets. 1.

The Semantic Web was invented by Tim Berners-Lee in 1998 as a web of data for machine consumption. Its applicability in supporting real world applications on the World Wide Web, however, remains unclear to this day because most existing works treat the Semantic Web as one universal RDF graph and ignore the Web aspect. In fact, the Semantic Web is distributed on the Web as a web of belief: each piece of Semantic Web data is independently published on the Web as a certain agent’s belief instead of the universal truth. Therefore, we enhance the current conceptual model of the Semantic Web to characterize both the content and the context of Semantic Web data. A significant sample dataset is harvested to demonstrate the non-trivial presence and the global properties of the Semantic Web on the Web. Based on the enhanced conceptual model, we introduce a novel search and navigation model for the unique behaviors in Web-scale Semantic Web data access, and develop an enabling tool – the Swoogle Semantic Web search engine. To evaluate the data quality of Semantic Web data, we also (i) develop an explainable ranking schema that orders the popularity of Semantic Web documents and terms, and (ii) introduce a new level of granularity of Semantic Web data – RDF molecule that supports lossless RDF graph decomposition and effective provenance tracking. This dissertation systematically investigates the Web aspect of the Semantic Web. Its primary contribu-tions are the enhanced conceptual model of the Semantic Web, the novel Semantic Web search and navigation model, and the Swoogle Semantic Web search engine.

Web search engines like Google have made people “smarter ” by providing ready access to the world's knowledge whenever they need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such information more accessible to computer programs by encoding it on the Web in

The computational analysis of protein-protein interaction and biomolecular pathway data paves the way to efficient in silico drug discovery and therapeutic target identification. However, relevant data sources are currently distributed across a wide range of disparate, large-scale, publicly-available databases and repositories and are described using a wide range of taxonomies and ontologies. Sophisticated integration, manipulation, processing and analysis of these datasets are required in order to reveal previously undiscovered interactions and pathways that will lead to the discovery of new drugs. The BioMANTA project focuses on utilizing Semantic Web technologies together with a scale-out architecture to tackle the above challenges and to provide efficient analysis, querying, and reasoning about protein-protein interaction data. This paper describes the initial results of the BioMANTA project. The fully-developed system will allow knowledge representation and processing that are not currently available in typical scale-out or Semantic Web databases. We present the design of the architecture, basic ontology and some implementation details that aim to provide efficient, scalable RDF storage and inferencing. The results of initial performance evaluation are also provided.

The provenance (i.e., origins) of information on the Web is crucial in many applications to allow information quality assessment, data integration, trust judgments, reproducibility, accountability, and many other important tasks. This document summarizes the positions of the W3C Provenance Incubator Group on the requirements to support provenance and their implications on the current implementation and future prospects of the W3C RDF standard.

Abstract. The increasing amount of interlinked RDF data has finally made available the necessary building blocks for the web of data. This in turns makes it possible (and interesting) to query such a collection of graphs as an open and decentralized knowledge base. However, despite the fact that there are already implementations of query answering algorithms for the web of data, there is no formal characterization of what a satisfactory answer is expected to be. In this paper, we propose a preliminary model for such an open collection of graphs which goes beyond the standard single-graph RDF semantics, describes three different ways in which a query can be answered, and characterizes them semantically in terms of three incremental restrictions on the relation between the domain of interpretation of each single component graph. 1