Research & Innovation

The most common format to store and provide technical documentation is PDF. However, due to the un- structured nature of the format these documents are often excluded from a granular semantic access.

This paper describes an OWL ontology that is a Universal Moral Grammar (UMG). UMG has been hypothesized by students of Chomsky to play the same role in human ethics as Universal Grammar (UG) does in Linguistics. I.e., the UMG describes an innate genetic phenotype of moral reasoning just as UG describes the Language Faculty.

rdf Stream Processing (rsp) is a rapidly evolving area of research that focuses on extensions of the Semantic Web in order to model and process Web data streams.

Rigorous evaluations and analyses of evaluation results are key towards improving Named Entity Linking systems. Nevertheless, most current evaluation tools are focused on benchmarking and comparative evaluations.

Energy from Waste (EfW) projects require complex value chains to operate effectively. To identify business partners, plant operators need to network with organisations whose strategic objectives are aligned with their own. Supplier organisations need to work out where they fit in the value chain.

While graph data on the Web and represented in RDF is growing, SPARQL, as the standard query language for RDF still remains largely unusable for the most typical graph query task: finding paths between selected nodes through the graph. Property Paths, as introduced in SPARQL1.1 turn out to be unfit for this task, as they can only be used for testing path existence and not even allow to count the number of paths between nodes. While such a feature has been shown to theoretically highly intractable, particularly in graphs with a high degree of cyclicity, practical use cases still demand a solution. A common restriction in fact is not to ask for all, but only the $k$-shortest paths between two nodes, in order to obtain at least the most important of potentially infeasibly many possible paths. In this paper, we extend SPARQL 1.1 property paths in a manner that allows to compute and return the $k$ shortest paths matching a property path expression between two nodes.

We present an algorithm and implementation and demonstrate in our evaluation that a realtively straightforward solution works (in fact, more efficiently than other, tailored solutions in the literature) in practical use cases.

Join operators are particularly important in SPARQL query engines that collect RDF data using Web access interfaces. State-of-the-art SPARQL query engines rely on binary join operators tailored for merging results from SPARQL queries over Web access interfaces.
However, in queries with a large number of triple patterns, binary joins constitute a significant burden on the query performance. 

Most of the existing Web user interfaces (UIs) are hard-coded by their developers to address certain predefined types of data, and hence are blind to the semantics of data they are dealing with. When talking about unstructured data or data without an explicit semantic representation, our expectations of data-awareness are lower. However, when we consider Linked Data UIs, where we have both structured data and semantics, we indeed expect more awareness from the UI which renders the data. In this paper we present an architecture for data-aware UIs, called Linked Data Reactor, implemented based on Web components and Semantic Web technologies. The proposed UIs can understand users' data and are capable to interact with users accordingly.

Currently, we are witnessing the rise of new technology-driven trends such as the Internet of Things, Web of Things, and Factories of the Future that are accompanied by an increasingly heterogeneous landscape of small, embedded, and highly modularized devices and applications, multitudes of manufactures and developers, and pervasion of things within all areas of life. At the same time, we can observe increasing complexity of the task of integrating subsets of heterogeneous components into applications that fulfil certain needs by providing value-added functionality beyond the pure sum of their components. Enabling integration in these multi-stakeholder scenarios requires new architectural approaches for adapting components, while building on existing technologies and thus ensuring broader acceptance. To this end, we present our approach on adaptation, that introduces adaptable interfaces, interactions, and processing for Linked Data Platform components. In addition, we provide an implementation of our approach that enables the adaptation of components via a thin meta-layer defined on top of the components' domain data and functionality. Finally, we evaluate our implementation by using a benchmark environment and adapting interfaces, interactions, and processing of the involved components at runtime.

Enhancing creativity has been paid much attention recently, especially with the emergence of online collaborative ideation. Prior work has shown that in addition to the exposure of diverse and creative examples, visualizing the solution space enables ideators to be inspired and thus, come-up with more creative ideas. However, existing automated approaches which assess the diversity of a set of examples fail on unstructured short text due to their reliance on similarity computation. Furthermore, the conceptual divergence cannot be easily captured for such representation. To overcome these issues, in this paper we introduce an ontology-based approach. The proposed solution formalizes user ideas into ontology-based concepts and then an ontology matching system is used to compute the similarity between users' ideas. Based on this approach, we aim also to create a visualization of the solution space based on the similarity matrix obtained by matching process between all ideas.