Hypermedia-based discovery for source selection using low-cost linked data interfaces

Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness

Detailed provenance capture of data processing

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Characterizing the Landscape of Musical Data on the Web: State of the Art and Challenges

Musical data can be analysed, combined, transformed and exploited for diverse purposes. However, despite the proliferation of digital libraries and repositories for music, infrastructures and tools, such uses of musical data remain scarce. As an initial step to help fill this gap, we present a survey of the landscape of musical data on the Web, available as a Linked Open Dataset: the musoW dataset of catalogued musical resources. We present the dataset and the methodology and criteria for its creation and assessment. We map the identified dimensions and parameters to existing Linked Data vocabularies, present insights gained from SPARQL queries, and identify significant relations between resource features. We present a thematic analysis of the original research questions associated with surveyed resources and identify the extent to which the collected resources are Linked Data-ready

Provenance in Linked Data Integration

The open world of the (Semantic) Web is a global information space offering diverse materials of disparate qualities, and the opportunity to re-use, aggregate, and integrate these materials in novel ways. The advent of Linked Data brings the potential to expose data on the Web, creating new challenges for data consumers who want to integrate these data. One challenge is the ability, for users, to elicit the reliability and/or the accuracy of the data they come across. In this paper, we describe a light-weight provenance extension for the voiD vocabulary that allows data publishers to add provenance metadata to their datasets. These provenance metadata can be queried by consumers and used as contextual information for integration and inter-operation of information resources on the Semantic Web

Help me describe my data: A demonstration of the Open PHACTS VoID Editor

Abstract. The Open PHACTS VoID Editor helps non-Semantic Web experts to create machine interpretable descriptions for their datasets. The web app guides the user, an expert in the domain of the data, through a series of questions to capture details of their dataset and then generates a VoID dataset description. The generated dataset description conforms to the Open PHACTS dataset description guidelines that en-sure suitable provenance information is available about the dataset to enable its discovery and reuse