Eye tracking is becoming more and more affordable, and thus gaze has the potential to become a viable input modality for human-computer interaction. We present the GazeEverywhere solution that can replace the mouse with gaze control by adding a transparent layer on top of the system GUI. It comprises three parts: i) the SPOCK interaction method that is based on smooth pursuit eye movements and does not suffer from the Midas touch problem; ii) an online recalibration algorithm that continuously improves gaze-tracking accuracy using the SPOCK target projections as reference points; and iii) an optional hardware setup utilizing head-up display technology to project superimposed dynamic stimuli onto the PC screen where a software modification of the system is not feasible. In validation experiments, we show that GazeEverywhere's throughput according to ISO 9241-9 was improved over dwell time based interaction methods and nearly reached trackpad level. Online recalibration reduced interaction target ('button') size by about 25%. Finally, a case study showed that users were able to browse the internet and successfully run Wikirace using gaze only, without any plug-ins or other modifications.

Easy reuse and integration of declaratively described information in a distributed setting is one of the main motivations for building the Semantic Web. Despite of this claim, reuse and recombination of RDF data today is mostly done using data replication and procedural code. A simple declarative mechanism for reusing and combining RDF data would help users to generate content for the semantic web. Having such a mechanism, the Semantic Web could better benefit from user generated content, as it is broadly present in the so called Web 2.0, but also from better linkage of existing content.We propose Networked Graphs, which allow users to define RDF graphs both, by extensionally listing content, but also by using views on other graphs. These views can be used to include parts of other graphs, to transform data before including it and to denote rules. The relationships between graphs are described declaratively using SPARQL queries and an extension of the SPARQL semantics. Networked Graphs are easily exchangeable between and interpretable on different computers. Using existing protocols, Networked Graphss can be evaluated in a distributed setting.