Utopia Documents

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Utopia Documents
Developer(s) Lost Island Labs Ltd., a spin-out from the University of Manchester
Development status Active
Operating system Microsoft Windows (XP, Vista, and Windows 7)
Mac (OS X 10.6 (Snow Leopard) and above
Platform Desktop computer, Laptop computer
Size 28.2 MB - Windows
33.8 MB - Mac
Type PDF Viewer / Reader
License Proprietary / Freeware
Website utopiadocs.com

Utopia Documents is a semantic, scientific, web-enabled PDF reader that is part of the Utopia toolset. Utopia Documents can be downloaded for free.[1][2][3][4][5]

The purpose of Utopia Documents is to help science move forward collaboratively. Because scientific knowledge is fragmented and often ‘buried’ in static content, there are many 'unknown knowns' in science. Much time is often wasted by repeating scientific experiments, by trying to verify facts, or by simply trying to find relevant further information. Utopia enables scientists to get the most from the scientific literature by providing links to appropriate web resources and metadata. Although Utopia is a PDF-reader, it bridges the web-connectivity gap with HTML content by making normally static PDFs fully web-enabled (as long as the user is online).

Versions[edit]

Utopia Documents v. 2.1 is available for Microsoft Windows (XP, Vista, and Windows 7) Mac (OS X 10.6 (Snow Leopard) and above and Linux (beta).

Software Features[edit]

Utopia Documents can be used in the same way as any other PDF reader, such as Adobe Acrobat Reader or the Preview application on a Mac. The application's workspace is split into three main panes (which can be collapsed): the PDF file itself is displayed on the left, a 'pager' is displayed at the bottom, and a sidebar to the right. The pager allows you to scan back and forth through the document and to move rapidly from one page to another. Although you can use Utopia Documents to look at any PDF file, the software really comes into its own as a reader for scholarly papers in the biomedical and biochemical fields.

  • Free PDF reader available for Windows, Mac and Linux (beta)
  • Recognizes a document by creating a unique ‘fingerprint’ of its contents as it is rendered and associates it with any version of the article even if it is a manuscript version deposited into an institutional repository
  • Fingerprints are created on the basis of interalia or key typographical and bibliometric characteristics (authors, figures, references etc.) A PDF is "transformed from a digital facsimile of its printed counterpart into a gateway to related knowledge, providing the research community with focused interactive access to analysis tools, external resources and the literature"
  • Direct link-outs from highlighted text to various data sources, scientific information, and search tools
  • Article impact metrics e.g. altmetrics are included when available to allow readers to view article data
  • Comments feature to allow researchers to make private comments or publicly discuss an article
  • Export of tables into spreadsheets and 'toggle' converting numerical tables into scatter plots
  • Optimized for life science-biomedical-biochemical scientific disciplines
  • Relies on external services; accessed via plug-ins whose appearance in the interface is mediated by a ‘semantic core’ for processing and analyzing data

Data Sources[edit]

The following data sources are accessed in Utopia Documents and activated automatically when there is relevant content to display:

References[edit]

  1. ^ Attwood, T. K.; Kell, D. B.; McDermott, P.; Marsh, J.; Pettifer, S. R.; Thorne, D. (2010). "Utopia documents: Linking scholarly literature with research data". Bioinformatics 26 (18): i568–i574. doi:10.1093/bioinformatics/btq383. PMC 2935404. PMID 20823323.  edit
  2. ^ Attwood, T. K.; Kell, D. B.; McDermott, P.; Marsh, J.; Pettifer, S. R.; Thorne, D. (2009). "Calling International Rescue: Knowledge lost in literature and data landslide!". Biochemical Journal 424 (3): 317–333. doi:10.1042/BJ20091474. PMC 2805925. PMID 19929850.  edit
  3. ^ Pettifer, S.; McDermott, P.; Marsh, J.; Thorne, D.; Villeger, A.; Attwood, T. K. (2011). "Ceci n'est pas un hamburger: Modelling and representing the scholarly article". Learned Publishing 24 (3): 207. doi:10.1087/20110309.  edit
  4. ^ Pafilis, E.; O'Donoghue, S. N. I.; Jensen, L. J.; Horn, H.; Kuhn, M.; Brown, N. P.; Schneider, R. (2009). "Reflect: Augmented browsing for the life scientist". Nature Biotechnology 27 (6): 508–510. doi:10.1038/nbt0609-508. PMID 19513049.  edit
  5. ^ http://journal.embnet.org/index.php/embnetnews/article/viewFile/45/180 Attwood TK. Utopia documents and the semantic Biochemical Journal experiment. EMBnet.journal. 2010;15(4).