(re)Funding Databases II

ResearchBlogging.orgSo, I wrote about defunding resources and briefly mentioned a paper in Database about funding (or ‘re’funding) databases and resources. I’d like to discuss this a bit further. The paper, by Chandras et. al, discusses how databases and, to use their term, Biological Resource Centers (BRCs) are to maintain financial viability.

Let me state first, I completely agree with their premise, that databases and resources have become imperative. The earlier model of “publication of experimental results and sharing of the reated research materials” needs to be extended. As they state:

It is however no longer adequate to share data through traditional modes of publication, and, particularly with high throughput (‘-omics) technologies, sharing of datasets requires submission to public databases as has long been the case with nucleic acid and protein sequence data.

The authors state, factually, that the financial model for most biological databases (we are talking the thousands that exist), has often been a 3-5 year development funding, that once runs out, the infrastructure needs to be supported by another source. In fact, this has lead to the defunding of databases such as TAIR and VBRC (and many others), excellent resources with irreplaceable data and tools, that then must struggle to find funding to maintain the considerable costs of funding infrastructure and continued development.

The demands of scientific research, open, shared data, require a funding model that maintains the publicly available nature of these databases. And thus the problem as they state:

If, for financial reasons, BRCs are unable to perform their tasks under conditions that meet the requirements of sceintfic research and the deamnds of industry, scientists will either see valuable information lost or being transferred into strictly commercial environment with at east two consequences: (i) blockade of access to this information and/or high costs and (ii) loss of data and potentioal for technology transfer for the foreseeable future. In either case the effect on both the scientific and broader community will be detrimental.

Again, I agree.

They discuss several possible solutions to maintaining the viability of publicly available databases including a private-public dual tier system where for-profits paid an annual fee and academic researchers have free access. They mention Uniprot, which underwent a funding crisis over a decade ago, as an example. Uniprot (then Swissprot) went back to complete public funding in 2002. There are still several other databases that are attempting to fund themselves by such a model. BioBase is one where several databases have been folded. TransFac is one. There is a free, reduced functionality, version that is available to academics through gene-regulation.com and the fuller version for a subscription at BioBase. This former version allows some data to be shared, as one could see at VISTA or UCSC. I am not privy to the financials of BioBase and other similar models, and I assume that will work for some, but I agree with the authors that many useful databases and resources would be hard-pressed to be maintained this way.

Other possibilities include fully  including databases under a single public institution funding mechanism. The many databases of NCBI and EBI fit this model. In fact, there is even a recent case of a resource being folded into this model at NCBI. Again, this works for some, but not all useful resources.

Most will have to find variable methods for funding their databases. Considering the importance of doing so, it is imperative that viable models are found. The authors reject, out of hand, advertising. As they mention, most advertisers will not be drawn to website advertising without a visibility of at least 10,000 visitors per month. There might be some truth to this (and I need to read the reference they cite that use to back that up).

But the next model they suggest seems to me to have the same drawback. In this model, the database or resource would have a ‘partnership of core competencies.’ An example they cite is MMdb (not to be confused with MMDB). This virtual mutant mouse repository provides direct trial links to Invitrogen from it’s gene information to the product page. They mention that though 6 companies were approached, only one responded. It would seem that this model has the same issues as directly selling advertising.

They also mention that, at least for their research community of mouse functional genomics, “Institutional Funding” seems the best solution for long-term viability and open access. Unfortunately, until institutions like NIH and EMBL are willing or able to fund these databases, I’m not sure that’s thats a solution.

As they mention in the paper, the rate of growth of the amounts and types of data that is being generated is exponential. I am not sure that government or institutional funding can financially keep up with housing the infrastructure needed to maintain and further develop these databases so that all the data generated can remain publicly and freely accessible.

Information is should be free, but unfortunately it is not without cost. It will be interesting to see how funding of databases and resources evolves in this fast growing genomics world (and imperative we figure out solutions).

PS: On a personal note, the authors use their resource, EMMA (European Mouse Mutant Archive), as an example in the paper. I like the name since it’s the name of my daughter, but it just goes to prove that names come in waves. We named our daughter thinking few would name their daughter the same. When even databases name the same name, you know that’s not the case.

Chandras, C., Weaver, T., Zouberakis, M., Smedley, D., Schughart, K., Rosenthal, N., Hancock, J., Kollias, G., Schofield, P., & Aidinis, V. (2009). Models for financial sustainability of biological databases and resources Database, 2009 DOI: 10.1093/database/bap017

2 thoughts on “(re)Funding Databases II

  1. Kevin Karplus

    It is not just databases that get tossed out. Web services that do computation also lose funding. I’m currently running the SAM_T08 web server for protein structure prediction and am obligated to keep it up because I announced in an NAR web-server issue, but I have had no funding for it for over a year. All attempts to get funding for the web service or for making a release version of the software so that someone else could duplicate the service have been denied. I’ve now given up wasting my time writing grant proposals for it, and I am maintaining it on my own time and using university techstaff to maintain the cluster (together this averages about an hour a week). When the hardware dies the service will die with it.

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