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Created Feb 11, 2014
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Four Postulates for Diagrams as Semantic Data Carriers in Scientific Publications

Four Postulates for Diagrams as Semantic Data Carriers in Scientific Publications

(this is an excerpt of the paper linked below)

We would like to take the opportunity to postulate the following actions, which we think should be carried out to make the content of images in biomedical articles more accessible:

  • Stop pressing diagrams into bitmaps! Unless the image only consists of one single photograph, screenshot, or another kind of picture that only has bitmap representation, vector graphics should be used for article figures.
  • Let data and metadata travel from the tools that generate diagrams to the final articles! Whenever the specific tool that is used to generate the diagram "knows" that a certain graphical element refers to an organism, a gene, an interaction, a point in time, or another kind of entity, then this information should be stored in the image file, passed on, and finally published with the article.
  • Use RDF vocabularies to embed semantic annotations in diagrams! Tools for creating scientific diagrams should use RDF notation and stick to existing standardized schemas (or define new ones if required) to annotate the diagram files they create.
  • Define standards for scientific diagrams! In the spirit of the Unified Modeling Language, the biomedical community should come up with standards that define the appearance and meaning of different types of diagrams.

Obviously, different groups of people need to be involved in these actions, namely article authors, journal editors, and tool developers. It is relatively inexpensive to follow these postulates (though it might require some time), which in turn would greatly improve data sharing, image mining, and scientific communication in general. Standardized diagrams could be the long sought solution to the problem of how to let authors publish computer-processable formal representations for (part of) their results.

Excerpt from: Tobias Kuhn, Mate Levente Nagy, ThaiBinh Luong, and Michael Krauthammer. Mining Images in Biomedical Publications: Detection and Analysis of Gel Diagrams. To appear in Journal of Biomedical Semantics. 2014.

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