Billions of Linked Data triples exist in thousands of RDF knowledge graphs on the Web, but few of those graphs can be queried live from Web applications. Only a limited number of knowledge graphs are available in a queryable interface, and existing interfaces can be expensive to host at high availability. To mitigate this shortage of live queryable Linked Data, we designed a low-cost Triple Pattern Fragments interface for servers, and a client-side algorithm that evaluates SPARQL queries against this interface. This article describes the Linked Data Fragments framework to analyze Web interfaces to Linked Data and uses this framework as a basis to define Triple Pattern Fragments. We describe client-side querying for single knowledge graphs and federations thereof. Our evaluation verifies that this technique reduces server load and increases caching effectiveness, which leads to lower costs to maintain high server availability. These benefits come at the expense of increased bandwidth and slower, but more stable query execution times. These results substantiate the claim that lightweight interfaces can lower the cost for knowledge publishers compared to more expressive endpoints, while enabling applications to query the publishers' data with the necessary reliability.

As the Web of Data is growing at an ever increasing speed, the lack of reliable query solutions for live public data becomes apparent. sparql implementations have matured and deliver impressive performance for public sparql endpoints, yet poor availability-especially under high loads-prevents their use in real-world applications. We propose to tackle this availability problem by defining triple pattern fragments, a specific kind of Linked Data Fragments that enable low-cost publication of queryable data by moving intelligence from the server to the client. This paper formalizes the Linked Data Fragments concept, introduces a client-side sparql query processing algorithm that uses a dynamic iterator pipeline, and verifies servers' availability under load. The results indicate that, at the cost of lower performance, query techniques with triple pattern fragments lead to high availability, thereby allowing for reliable applications on top of public, queryable Linked Data.

Abstract. Applications built on top of the Semantic Web are emerging as a novel solution in different areas, such as decision making and route planning. However, to connect results of these solutions -i.e., the semantically annotated data -with real-world applications, this semantic data needs to be connected to actionable events. A lot of work has been done (both semantically as non-semantically) to describe and define Web services, but there is still a gap on a more abstract level, i.e., describing interfaces independent of the technology used. In this paper, we present a data model, specification, and ontology to semantically declare and describe functions independently of the used technology. This way, we can declare and use actionable events in semantic applications, without restricting ourselves to programming language-dependent implementations. The ontology allows for extensions, and is proposed as a possible solution for semantic applications in various domains.

Abstract. Mapping languages allow us to define how Linked Data is generated from raw data, but only if the raw data values can be used as is to form the desired Linked Data. Since complex data transformations remain out of scope for mapping languages, these steps are often implemented as custom solutions, or with systems separate from the mapping process. The former data transformations remain case-specific, often coupled with the mapping, whereas the latter are not reusable across systems. In this paper, we propose an approach where data transformations (i) are defined declaratively and (ii) are aligned with the mapping languages. We employ an alignment of data transformations described using the Function Ontology (fno) and mapping of data to Linked Data described using the rdf Mapping Language (rml). We validate that our approach can map and transform dbpedia in a declaratively defined and aligned way. Our approach is not case-specific: data transformations are independent of their implementation and thus interoperable, while the functions are decoupled and reusable. This allows developers to improve the generation framework, whilst contributors can focus on the actual Linked Data, as there are no more dependencies, neither between the transformations and the generation framework nor their implementations.

Linked Data is often generated based on a set of declarative rules using languages such as R2RML and RML. These languages are built with machine-processability in mind. It is thus not always straightforward for users to define or understand rules written in these languages, preventing them from applying the desired annotations to the data sources. In the past, graphical tools were proposed. However, next to users who prefer a graphical approach, there are users who desire to understand and define rules via a text-based approach. For the latter, we introduce an enhancement to their workflow. Instead of requiring users to manually write machine-processable rules, we propose writing human-friendly rules, and generate machine-processable rules based on those human-friendly rules. At the basis is YARRRML: a human-readable text-based representation for declarative generation rules. We propose a novel browser-based integrated development environment (IDE) called Matey, showcasing the enhanced workflow. In this work, we describe our demo. Users can experience first hand how to generate triples from data in different formats by using YARRRML's representation of the rules. The actual machine-processable rules remain completely hidden when editing. Matey shows that writing human-friendly rules enhances the workflow for a broader range of users. As a result, more desired annotations will be added to the data sources which leads to more desired Linked Data.

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The overall majority of books are currently being made with primarily a printed outcome in mind. To make a digital version of these books, most manuscripts need to be reprocessed , which usually results in customary built e-books. This need for a customized authoring workflow for every electronic version of a book makes it impossible to build e-books in a cost-effective way. In this paper, we propose a novel workflow that incorporates both print and digital book authoring. By charting the currently most widespread workflow Flemish publishers use to author print books and e-books, we are able to identify the most pressing problems. These are the print-first approach, the vendor lock-in situation of the e-reader market, and the high cost of updating and/or maintaining the content of an (e-)book. To overcome the aforementioned problems, we devise a new workflow that follows a digital-first approach using Open Web standards, separating content, structure, and layout. We evaluate the proposed workflow by building a proof-of-concept authoring environment. Using this new workflow, both digital and print books can be built without significant additional costs. The proof of concept is evaluated using an experts group of Flemish publishers, and received general positive reception, with concerns on how to incorporate the proposed workflow into production environments. By not limiting the proof of concept to a fixed data model, it could handle content from more content providers, facilitating further research into the possibilities and future requirements of the EPUB 3 specification.

Abstract. The success of the Semantic Web highly depends on its ingredients. If we want to fully realize the vision of a machine-readable Web, it is crucial that Linked Data are actually useful for machines consuming them. On this background it is not surprising that (Linked) Data validation is an ongoing research topic in the community. However, most approaches so far either do not consider reasoning, and thereby miss the chance of detecting implicit constraint violations, or they base themselves on a combination of dierent formalisms, eg Description Logics combined with SPARQL. In this paper, we propose using Rule-Based Web Logics for RDF validation focusing on the concepts needed to support the most common validation constraints, such as Scoped Negation As Failure (SNAF), and the predicates dened in the Rule Interchange Format (RIF). We prove the feasibility of the approach by providing an implementation in Notation3 Logic. As such, we show that rule logic can cover both validation and reasoning if it is expressive enough.