Modeling and querying graphical representations of statistical data

Although pictorial renditions of statistical data are ubiquitous, few techniques and standards exist to exchange, search and query these graphical representations. We present several improvements to human-graph interaction including i) a new approach to manage statistical graph knowledge by semantic annotation of graphs that bridges the gap between Web 2.0 social tagging and formal, logic-based approaches, ii) knowledge management and discovery across a non-trivial graph knowledge base and iii) sophisticated question answering that requires background knowledge using Semantic Web technology.