title: Utopia documents: linking scholarly literature with research data.
abstract: BACKGROUND
  In recent years, the gulf between the mass of accumulating-research data and the massive literature describing and analyzing those data has widened. The need for intelligent tools to bridge this gap, to rescue the knowledge being systematically isolated in literature and data silos, is now widely acknowledged.
  
  
  RESULTS
  To this end, we have developed Utopia Documents, a novel PDF reader that semantically integrates visualization and data-analysis tools with published research articles. In a successful pilot with editors of the Biochemical Journal (BJ), the system has been used to transform static document features into objects that can be linked, annotated, visualized and analyzed interactively (http://www.biochemj.org/bj/424/3/). Utopia Documents is now used routinely by BJ editors to mark up article content prior to publication. Recent additions include integration of various text-mining and biodatabase plugins, demonstrating the system's ability to seamlessly integrate on-line content with PDF articles.
  
  
  BACKGROUND
  http://getutopia.com.
authors.affiliation: School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk
authors.forename: T K
authors.initials: TK
authors.lastname: Attwood
authors.forename: D B
authors.initials: DB
authors.lastname: Kell
authors.forename: P
authors.initials: P
authors.lastname: McDermott
authors.forename: J
authors.initials: J
authors.lastname: Marsh
authors.forename: S R
authors.initials: SR
authors.lastname: Pettifer
authors.forename: D
authors.initials: D
authors.lastname: Thorne
mesh_terms: D007255:Information Services; D020407:Internet; D008091:Literature; D010506:Periodicals as Topic; D011642:Publications / Q000145:classification; D011643:Publishing; D012106:Research; D012984:Software
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