Afzal M. T., Latif A., Us Saeed A., Sturm P., Aslam S., Andrews K., Maurer H.
2009
Discovery and Visualization of Expertise in a Scientific Community
Proceedings of the International Conference on Frontiers of Information Technology (FIT 2009)
In numerous contexts and environments, it is necessary to identify
and assign (potential) experts to subject fields. In the context of
an academic journal for computer science (J.UCS), papers and
reviewers are classified using the ACM classification scheme.
This paper describes a system to identify and present potential
reviewers for each category from the entire body of paper’s
authors. The topical classification hierarchy is visualized as a
hyperbolic tree and currently assigned reviewers are listed for a
selected node (computer science category). In addition, a spiral
visualization is used to overlay a ranked list of further potential
reviewers (high-profile authors) around the currently selected
category. This new interface eases the task of journal editors in
finding and assigning reviewers. The system is also useful for
users who want to find research collaborators in specific research
areas.
Latif A., Afzal M. T., Höfler Patrick, Us Saeed A.
2009
Turning Keywords into URIs: Simplified User Interfaces for Exploring Linked Data
ACM Proceeding of ICIS 2009. ISBN: 978-1-60558-710-3
The Semantic Web strives to add structure and meaning to the Web, thereby providing better results and easier interfaces for its users. One important foundation of the Semantic Web is Linked Data, the concept of interconnected data, describing resources by use of RDF and URIs. Linked Data (LOD) provides the opportunity to explore and combine datasets on a global scale -- something which has never been possible before. However, at its current stage, the Linked Data cloud yields little benefit for end users who know nothing of ontologies, triples and SPARQL. This paper presents an intelligent technique for locating desired URIs from the huge repository of Linked Data. Search keywords provided by users are utilized intelligently for locating the intended URI. The proposed technique has been applied in a simplified end user interface for LOD. The system evaluation shows that the proposed technique has reduced user's cognitive load in finding relevant information.