Rating, Recognizing and Rewarding Metadata Integration and Sharing on the Semantic Web

The diagram and data source sharing features lay the foundation for collab- orative work enabling multiple users to construct the views based on common data together and in

With the recent advances in deep learning, i.e., in subsymbolic approaches, questions how to interface these methods with symbolic data or systems resurface with renewed urgency,

This integration is often a significant cost factor due to the wide variance regarding rep- resentational choices for data, ranging from syntactic data formats to semantic

We wish to devise a mapping strategy that will allow Semantic Web based knowledge bases to be exposed using the Ondex data model because of the rich feature set that Ondex

These ordering descriptions were then used to build description indices, tree-based indices over databases consisting of sets of descriptions, with performance guarantees on

– If a node x contains instances of different concepts, this node is annotated using an instance of PartOfSpeech metadata : we add the fact isAnnotat- edBy(x,i), partOfSpeech(i),

Based on the ramm.x use cases 6 , we have identified several issues that will be addressed by future extensions 7 : (i) collect formalisations of different multimedia

Validating Revyu data against external sources not only allows the derivation of more reliable type information than would be possible using tags alone, it also allows items on