The DBpedia project is a community effort to extract structured information from Wikipedia and to make this information accessible on the Web. The resulting DBpedia knowledge base currently describes over 2.6 million entities. For each of these entities, DBpedia defines a globally unique identifier that can be dereferenced over the Web into a rich RDF description of the entity, including human-readable definitions in 30 languages, relationships to other resources, classifications in four concept hierarchies, various facts as well as data-level links to other Web data sources describing the entity. Over the last year, an increasing number of data publishers have begun to set data-level links to DBpedia resources, making DBpedia a central interlinking hub for the emerging Web of data. Currently, the Web of interlinked data sources around DBpedia provides approximately 4.7 billion pieces of information and covers domains such as geographic information, people, companies, films, music, genes, drugs, books, and scientific publications. This article describes the extraction of the DBpedia knowledge base, the current status of interlinking DBpedia with other data sources on the Web, and gives an overview of applications that facilitate the Web of Data around DBpedia.

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: Linked Open Data has become one of the driving forces for the emerging Semantic Web, which enables interlinking and integrating former proprietary data to the global linked data by using RDF as a standard data format. In this paper we show how to integrate the database of the open academic video search plattform yovisto.com with the linked open data cloud and how to augment yovisto video search by including semantically interrelated linked open data.

Abstract. In this paper we present a Web-based system for annotating digitised old maps. Using bibliographic metadata and geographical reference information associated with the map, annotations are represented as spatially and temporally defined RDF resources. At the same time, named entity recognition and semantic link discovery are applied to each annotation’s text content to further facilitate its interlinking within the Web of Data. To ensure quality and correctness, the system relies on human feedback. This feedback is introduced through a novel interaction metaphor: contextual link suggestions are continuously generated in the background, and superimposed on the annotated map region in the form of a tag cloud. The user can create semantic links by simply clicking on the corresponding tags. The system thus acts both as a visualisation aid for contextually relevant linked data and as a tool for authoring new linked spatiotemporal data entities.

Abstract. The rising popularity of RESTful Web services has recently motivated the extension of existing service orchestration engines to support the composition of services that do not rely on machine-readable descriptions. At the same time, within the Linking Open Data initiative, data sets are published conforming to the Linked Data principles, which can be naturally achieved by exposing RDF data through RESTful interfaces. In this position paper, we motivate the use of service orchestration to define workflows for interlinking open data. We introduce the design of an abstract workflow for the semantic enrichment of such data with the purpose of providing an integrated view on otherwise isolated data sources. Finally, based on this abstract workflow we present early work on a concrete implementation and report on our experiences. 1

Abstract: Linked Data is as essential for the Semantic Web as hypertext has been for the Web. For this reason, the W3C community project Linking Open Data has been facilitating the transformation of publicly available, open data into Linked Data since 2007. As of 2009, the vast majority of Linked Data is still generated by research communities and institutions. For a successful corporate uptake, we deem it important to have a strong conceptual groundwork, providing the foundation for the development of business cases revolving around the adoption of Linked Data. We therefore present the Linked Data Value Chain, a model that conceptualizes the current Linked Data sphere. The Linked Data Value Chain helps to identify and categorize potential pitfalls which have to be considered by business engineers. We demonstrate this process within a concrete case study involving the BBC.

The promise of the Semantic Web is to democratise access to data, allowing anyone to make use of and contribute back to the global store of knowledge. Within the scope of the OMRAS2 Music Information Retrieval project, we have made use of and contributed to Semantic Web technologies for purposes ranging from the publication of music recording metadata to the online dissemination of results from audio analysis algorithms. In this paper, we assess the extent to which our tools and frameworks can assist in research and facilitate distributed work among audio and music researchers, and enumerate and motivate further steps to improve collaborative efforts in music informatics using the Semantic Web. To this end, we review some of the tools developed by the OMRAS2 project, examine the extent to which our work reflects the Semantic Web paradigm, and discuss some of the remaining work needed to fulfil the promise of online music informatics research. 1

Abstract. Many systems exist for community formation in extensions of traditional Web environments but little work has been done for forming and maintaining communities in the more dynamic environments emerging from ad hoc and peer-to-peer networks. This paper proposes an approach for forming and evolving peer communities based on the sharing of choreography specifications (Interaction Models (IMs)). Two mechanisms for discovering IMs and collaborative peers are presented based on a meta-search engine and a dynamic peer grouping algorithm respectively. OKBook, a system allowing peers to publish, discover and subscribe or unsubscribe to IMs, has been implemented in accordance with our approach. For the meta-search engine, a strategy for integrating and re-ranking search results obtained from Semantic Web search engines is also described. This allows peers to discover IMs from their group members, thus reducing the burden on the meta-search engine. Our approach complies with principles of Linked Data and is capable of both contributing to and benefiting from the Web of data. 1

Abstract. In this paper we present our current experience of aggregating user data from various Social Web applications and outline several key challenges in this area. The work is based on a concrete use case: reusing activity streams to determine a viewer’s interests and generating television programme recommendations from these interests. Three system components are used to realise this goal: (1) an intelligent remote control: iZapper for capturing viewer activities in a cross-context television environment; (2) a backend: BeanCounter for aggregation of viewer activities from the iZapper and from different social web applications; and (3) a recommendation engine: iTube for recommending relevant television programmes. The focus of the paper is the BeanCounter as the first step to apply Social Web data for viewer and context modelling on the Web. This is work in progress of the NoTube project 4. 1

The DBpedia project has extracted a rich knowledge base from Wikipedia and serves this knowledge base as Linked Data on the Web. DBpedia’s knowledge base currently provides 274 million pieces of information about 2.6 million concepts. As DBpedia covers a wide range of domains and has a high degree of conceptual overlap with various openlicense datasets that are already available on the Web, an increasing number of data publishers has started to set data links from their data sources to DBpedia, making DBpedia one of the central interlinking hubs of the emerging Web of Data. This paper gives an overview about the DBpedia project and describes how application developers can make use of DBpedia knowledge within their applications.