Article: The Economics of Reproducibility in Preclinical Research

Posted: June 15th, 2015 | Author: | Filed under: found on the net, Research Data | Tags: , , , | Comments Off on Article: The Economics of Reproducibility in Preclinical Research

preclinical_250_AIDSVaccine_flickrIn 2012, an estimated 114.8 billion $ in the US were spent on life sciences research. Roughly half of it is spent on preclinical research, with government sources providing the majority of funding – approximatly 38 billion US$.

Now, three researchers calculate the costs of irreproducible research in preclinical research near 28 billion $ – only for the United States alone.┬áThat is the conclusion of a study published in PLoS Biology a few days ago.

In the opinion of the study’s authors, the giant amount of 28 billion $ accumulates, because low reproducibility rates within life science research undermine cumulative knowledge production and contribute to both delays and costs of therapeutic drug development.

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SageCite-Project releases interviews with biosciences editors on citing and linking data

Posted: December 5th, 2011 | Author: | Filed under: Projects | Tags: , , , , , | 1 Comment »
The SageCite project, funded by JISC, is releasing interviews with the editors of two leading journals in the Biosciences.  The two interviews explore a large range of issues concerning data, scholarly communications and publishers, the links between data and publications and interoperability between data repositories and publishers.
SageCite developed and tested a Citation Framework linking data, methods and publications; Citations of complex network models of disease and associated data have been embedded in leading publications, exploring issues around the citation of data including the compound nature of datasets, description standards and identifiers.

The project worked through a number of workpackages comprising:

* Review and evaluation of options and approaches for data citation
* Understanding the requirements for citing large-scale network models of disease and compound research obejcts
* Demonstration of a citation-enabled workflow using a linked data approach
* Benefits mapping using the “Keeping Research Data Safe 2” taxonomy
* Technical and policy implications of citation by leading publishers
* Dissemination across communities (bio-informatics and research and information communities)

The results of these workpackages are published here – the project now has concluded.