Abstract
Millions of life scientists across the world rely on bioinformatics data resources for their research projects. Data resources can be very expensive, especially those with a high added value as the expert-curated knowledgebases. Despite the increasing need for such highly accurate and reliable sources of scientific information, most of them do not have secured funding over the near future and often depend on short-term grants that are much shorter than their planning horizon. Additionally, they are often evaluated as research projects rather than as research infrastructure components. In this work, twelve funding models for data resources are described and applied on the case study of the Universal Protein Resource (UniProt), a key resource for protein sequences and functional information knowledge. We show that most of the models present inconsistencies with open access or equity policies, and that while some models do not allow to cover the total costs, they could potentially be used as a complementary income source. We propose the Infrastructure Model as a sustainable and equitable model for all core data resources in the life sciences. With this model, funding agencies would set aside a fixed percentage of their research grant volumes, which would subsequently be redistributed to core data resources according to well-defined selection criteria. This model, compatible with the principles of open science, is in agreement with several international initiatives such as the Human Frontiers Science Program Organisation (HFSPO) and the OECD Global Science Forum (GSF) project. Here, we have estimated that less than 1% of the total amount dedicated to research grants in the life sciences would be sufficient to cover the costs of the core data resources worldwide, including both knowledgebases and deposition databases.
Highlights
1 Introduction Knowledgebases, why? Knowledgebases are organized and dynamic collections of information about a particular subject where data from multiple sources are archived, and reviewed, distilled and manually annotated by experts. These digital infrastructures are essential to the effective functioning of scientific research and for the whole life science community: they serve as encyclopaedias, concentrating high quality knowledge collected from many different sources
SwissProt returned to an all-user-free access model in 2004 after the SIB Swiss Institute of Bioinformatics, the European Bioinformatics Institute (EMBL-EBI), and the Protein Information Resource (PIR) formed the Universal Protein Resource (UniProt) consortium and obtained a grant from the National Institutes of Health (NIH)
The UniProt knowledgebase is an interesting case study because it passed through various funding models, as well described in the literature[7,18,19]
Summary
1. Helen Berman, Rutgers, The State University of New Jersey , Piscataway, USA John Westbrook, The State University of New Jersey, Piscataway, USA. 2. Eva Huala, Phoenix Bioinformatics, Redwood City, USA Arabidopsis Information Resource, Redwood City, USA Tanya Z. Berardini , Phoenix Bioinformatics, Redwood City, USA The Arabidopsis Information Resource, Redwood City, USA. Article can be found at the end of the article. This article is included in the ELIXIR gateway
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