Michele Pasin / Quotes

Problems caused by the digital revolution in scientific publishing

During the past two decades the ecosystem of biomedical publications has moved from a print-based to a mainly Web-based model. However, this transition brings with it many new problems, in the context of an exponentially increasing, intractable volume of publications [1,2]; of systemic problems relating to valid (or invalid) citation of scientific evidence [3,4]; rising levels of article retractions [5,6] and scientific misconduct [7]; of uncertain reproducibility and re-usability of results in therapeutic development [8], and lack of transparency in research publication [9]. While we now have rapid access to much of the world’s biomedical literature, our methods to organize, verify, assess, combine and absorb this information in a comprehensive way, and to move discussion and annotation activities through the ecosystem efficiently, remain disappointing. [...] Computational methods previously proposed as solutions include ontologies [10]; text mining [2,11,12]; databases [13]; knowledgebases [14]; visualization [15]; new forms of publishing [16]; digitial abstracting [1]; semantic annotating [17]; and combinations of these approaches. However, we lack a comprehensive means to orchestrate these methods. We propose to accomplish this with a layered metadata model of scientific argumentation and evidence.

Saved 26 November 2014 / www.jbiomedsem.com ↗

#metadata-model #text-mining

Digital libraries beyond search and access

...going "beyond search and access" while not ignoring these functions has already been explored in Lagoze, et al. (2005). The authors argue that digital…

Core : Three Access Levels To Underpin Open Access #services #metadata-model #digital-libraries #resources #raw-data

Literature-based discovery (lbd)

Not only are text-mining and information extraction tools needed to render the biomedical literature accessible but the results of these tools can also assist…

Online Tools To Support Literature-based Discovery In The Life Sciences #tool #text-mining