CAF-SIAL: Concept aggregation framework for structuring informational aspects of linked open data

Linked Open Data (LOD) is becoming an essential part of the Semantic Web. Although LOD has amassed large quantities of structured data from diverse, openly available data sources, there is still a lack of user-friendly interfaces and mechanisms for exploring this huge resource. In this paper we highlight two critical issues related to the exploration of the semantic LOD pool by end users. We introduce a proof of concept application which helps users to search information about a concept without having to know the mechanics of the Semantic Web or Linked Data. We assume that this kind of application may lead to bridge the gap between semantic search and end users. With this application, we concentrated on two aspects: 1) A novel Concept Aggregation Framework to present the most relevant information of LOD resources in an easy to understand way. 2) A simplified search mechanism which hides the complex underlying semantic search logic. This research is intended to simplify the LOD end user interfaces so that they may be used by novice users who don´t possess any prior knowledge of semantic structures.