Abstract. One of the major obstacles for a wider usage of web data is the difficulty to obtain a clear picture of the available datasets. In order to reuse, link, revise or query a dataset published on the Web it is important to know the structure, coverage and coherence of the data. In order to obtain such information we developed LODStats -a statement-stream-based approach for gathering comprehensive statistics about datasets adhering to the Resource Description Framework (RDF). LODStats is based on the declarative description of statistical dataset characteristics. Its main advantages over other approaches are a smaller memory footprint and significantly better performance and scalability. We integrated LODStats with the CKAN dataset metadata registry and obtained a comprehensive picture of the current state of a significant part of the Data Web.

Abstract. This demo presents LODStats, a web application for collection and exploration of the Linked Open Data statistics. LODStats consists of two parts: the core collects statistics about the LOD cloud and publishes it on the LODStats web portal, a front-end for exploration of dataset statistics. Statistics are published both in human-readable and machine-readable formats, thus allowing consumption of the data through web front-end by the users as well as through an API by services and applications. As an example for the latter we showcase how to visualize the statistical data with the CubeViz application.

The LOD2 Stack is an integrated distribution of aligned tools which support the whole life cycle of Linked Data from extraction, authoring/creation via enrichment, interlinking, fusing to maintenance. The LOD2 Stack comprises new and substantially extended existing tools from the LOD2 project partners and third parties. The stack is designed to be versatile; for all functionality we define clear interfaces, which enable the plugging in of alternative third-party implementations. The architecture of the LOD2 Stack is based on three pillars: (1) Software integration and deployment using the Debian packaging system. (2) Use of a central SPARQL endpoint and standardized vocabularies for knowledge base access and integration between the different tools of the LOD2 Stack. (3) Integration of the LOD2 Stack user interfaces based on REST enabled Web Applications. These three pillars comprise the methodological and technological framework for integrating the very heterogeneous LOD2 Stack components into a consistent framework. In this article we describe these pillars in more detail and give an overview of the individual LOD2 Stack components. The article also includes a description of a real-world usage scenario in the publishing domain.

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Abstract. The performance of triple stores is one of the major obstacles for the deployment of semantic technologies in many usage scenarios. In particular, Semantic Web applications, which use triple stores as persistence backends, trade performance for the advantage of flexibility with regard to information structuring. In order to get closer to the performance of relational database-backed Web applications, we developed an approach for improving the performance of triple stores by caching query results and even complete application objects. The selective invalidation of cache objects, following updates of the underlying knowledge bases, is based on analysing the graph patterns of cached SPARQL queries in order to obtain information about what kind of updates will change the query result. We evaluated our approach by extending the BSBM triple store benchmark with an update dimension as well as in typical Semantic Web application scenarios.