The explosion of scientific data coming from high throughput experimental methods has lead to the creation of several new databases for biological information (protein structures, genomes, metabolic networks and kinetic rates, expression data, protein interactions, etc). Given that funding is generally attributed for a limited time and for defined projects it is possible to obtain money to start a database project but it very difficult to obtain a stable source of funding to sustain a useful database. I mentioned this before more than once when talking about the funding problems of BIND.
In this issue of The Scientist there is a short white paper entitle "Save our Data!". It details the recommendations of The Plant Genome Database Working Group for the problems currently faced by the life science databases.
I emphasize here four point they make:
2. Develop a funding mechanism that would support biological databases for longer cycle times than under current mechanisms.
3. Foster curation as a career path.
6. Separate the technical infrastructure from the human infrastructure. Many automated computational tasks do not require specialized species- or clade-specific knowledge.
7. Standardize data formats and user interfaces.
The first and last points were also discussed a recent editorial in Nature Biotech.
What was a bit of a surprise for me is their 3rd point on fostering curation as career path. Is it really necessary to have professional curators ? I am a bit divided between a more conservative approach at data curation with a team of professional curators or a wisdom of the crowds type of approach were tools are given to the communities and they solve the curation problems. I think it would be more efficient to find ways to have the people producing the data, curating it automatically into the databases. To have this happen it has to be really easy and immediate to do. I still think that journals are the only ones capable of enforcing this process.
The 6th point they make is surely important even if the curation effort are to be pushed back to the people producing the data. It is important to make the process of curating the data as automatic and easy as possible.