The term Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions- the Web of Data. In this article we present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. We describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

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 Furthermore, we describe how this metadata can be queried and consumed to identify outdated information. 1

During recent years an increasing number of data providers adopted the Linked Data principles for publishing and connecting structured data on the Web, thus creating a globally distributed dataspace – the Web of Data. While the execution of structured, SQL-like queries over this dataspace opens possibilities not conceivable before, query execution on the Web of Data poses novel challenges. These challenges provide great opportunities for the database community. In this article we introduce the concept of Linked Data and discuss different approaches to query the Web of Data. Our goal is to provide a general understanding of this new research area and of the challenges and open issues that must be addressed.

Abstract. The Web of Linked Data is built upon the idea that data items on the Web are connected by RDF links. Sadly, the reality on the Web shows that Linked Data sources set some RDF links pointing at data items in related data sources, but they clearly do not set RDF links to all data sources that provide related data. In this paper, we present Silk Server, an identity resolution component, which can be used within Linked Data application architectures to augment Web data with additional RDF links. Silk Server is designed to be used with an incoming stream of RDF instances, produced for example by a Linked Data crawler. Silk Server matches the RDF descriptions of incoming instances against a local set of known instances and discovers missing links between them. Based on this assessment, an application can store data about newly discovered instances in its repository or fuse data that is already known about an entity with additional data about the entity from the Web. Afterwards, we report on the results of an experiment in which Silk Server was used to generate RDF links between authors and publications from the Semantic Web Dog Food Corpus and a stream of FOAF profiles that were crawled from the Web.

Publishing and consuming content on the Web of Data often requires considerable expertise in the underlying technologies, as the expected services to achieve this are either not packaged in a simple and accessible manner, or are simply lacking. In this poster, we address selected issues by briefly introducing the following essential Web of Data services designed to lower the entry-barrier for Web developers: (i) a multi-ping service, (ii) a meta search service, and (iii) a universal discovery service.

Abstract. With the growing numbers of status update websites and related wrappers, initiatives modelling sensor data in RDF, as well as the dynamic nature of many Linked Data exporters, there is a need for protocols enabling real-time notification and broadcasting of RDF data updates. In this paper we present a flexible approach that provides such notifications to be delivered in real-time to any RSS or Atom reader. Our framework enables the active delivery of SPARQL query results through the PubSubHubbub (PuSH) protocol upon the arrival of new information in RDF stores. Our open source implementation can be plugged on any SPARQL endpoint and can directly reuse PuSH hubs that are already deployed in scalable clouds (e.g. Google’s). 1

Whether it's population, income, unemployment or interest rates, statistical data is a fundamental source of information for analysis and visualisations. Many publishers of statistics use SDMX to represent statistics and make them available through web services. The linked data principles of identifying items with HTTP URIs and representing data using RDF provide some benefits (though also some costs) for statistical publishing. This paper describes how the SDMX information model can be used with linked data and RDF and describes some ongoing work to explore the impact of doing so.

Abstract. In this paper, we present a project which extends a SMW+ semantic wiki with a Linked Data Integration Framework that performs Web data access, vocabulary mapping, identity resolution, and quality evaluation of Linked Data. As a result, a large collection of neurogenomicsrelevant data from the Web can be flexibly transformed into a unified ontology, allowing unified querying, navigation, and visualization; as well as support for wiki-style collaboration, crowdsourcing, and commentary on chosen data sets.

Abstract—Provenance is a cornerstone element in the process of enabling quality assessment for the Web of Data. Applications consuming or generating Linked Data will need to become provenance-aware, i.e., being able to capture and consume provenance information associated with the data. This will bring provenance as a key requirement for a wide spectrum of applications. This work describes Prov4J, a framework which uses Semantic Web tools and standards to address the core challenges in the construction of a generic provenance management system. The work discusses key software engineering aspects for provenance capture and consumption and analyzes the suitability of the framework under the deployment of a real-world scenario. Keywords- provenance management; semantic web. I.

Abstract—This paper describes a Semantic Web (SW) model for gene lists and the metadata required for their practical interpretation. Our provenance information captures the context of experiments as well as the processing and analysis parameters involved in deriving the gene lists from DNA microarray experiments. We demonstrate a range of practical neuroscience queries which draw on the proposed model. Our provenance representation includes the origins of the gene list and basic information about the data set itself (e.g. last modification date and original data source), in order to facilitate the federation of gene lists with other types of Semantic Web-formatted data and include the integration of a broader molecular context through additional omics data. Keywords-data integration, query federation, semantic web I.