ArticleDatabase : the journal of biological databases and curation2010
The annotation and the usage of scientific databases could be improved with public issue tracker software.
Article in Database : the journal of biological databases and curation, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- CONNJUR R: an annotation strategy for fostering reproducibility in bio-NMR-protein spectral assignment.Journal of biomolecular NMR · 2015Article
- A system-level, molecular evolutionary analysis of mammalian phototransduction.BMC evolutionary biology · 2013Article
- Solving the Problem: Genome Annotation Standards before the Data Deluge.Standards in genomic sciences · 2011Article
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Authors and funding
3 authors.
Funding
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Abstract
Since the publication of their longtime predecessor The Atlas of Protein Sequences and Structures in 1965 by Margaret Dayhoff, scientific databases have become a key factor in the organization of modern science. All the information and knowledge described in the novel scientific literature is translated into entries in many different scientific databases, making it possible to obtain very accurate information on a biological entity like genes or proteins without having to manually review the literature on it. However, even for the databases with the finest annotation procedures, errors or unclear parts sometimes appear in the publicly released version and influence the research of unaware scientists using them. The researcher that finds an error in a database is often left in a uncertain state, and often abandons the effort of reporting it because of a lack of a standard procedure to do so. In the present work, we propose that the simple adoption of a public error tracker application, as in many open software projects, could improve the quality of the annotations in many databases and encourage feedback from the scientific community on the data annotated publicly. In order to illustrate the situation, we describe a series of errors that we found and helped solve on the genes of a very well-known pathway in various biomedically relevant databases. We would like to show that, even if a majority of the most important scientific databases have procedures for reporting errors, these are usually not publicly visible, making the process of reporting errors time consuming and not useful. Also, the effort made by the user that reports the error often goes unacknowledged, putting him in a discouraging position.
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