Modeling and querying graphical representations of statistical data

  • Authors:
  • Michel Dumontier;Leo Ferres;Natalia Villanueva-Rosales

  • Affiliations:
  • Department of Biology, Carleton University, Ottawa, Canada and School of Computer Science, Carleton University, Ottawa, Canada;Department of Computer Science, University of Concepción, Concepción, Chile;School of Computer Science, Carleton University, Ottawa, Canada

  • Venue:
  • Web Semantics: Science, Services and Agents on the World Wide Web
  • Year:
  • 2010

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Abstract

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.