Financing a future for public biological data

Citation
Lbm. Ellis et D. Kalumbi, Financing a future for public biological data, BIOINFORMAT, 15(9), 1999, pp. 717-722
Citations number
26
Categorie Soggetti
Multidisciplinary
Journal title
BIOINFORMATICS
ISSN journal
13674803 → ACNP
Volume
15
Issue
9
Year of publication
1999
Pages
717 - 722
Database
ISI
SICI code
1367-4803(199909)15:9<717:FAFFPB>2.0.ZU;2-D
Abstract
Motivation: The public web-based biological database infrastructure is a so urce of both wonder and worry. Users delight in the ever increasing amounts of information available, database administrators and curators worry about long-term financial support. AM earlier study of 153 biological databases (Ellis and Kalumbi, Nature Biotechnol., Id, 1323-1324, 1998) determined tha t near future (1-5 year) funding for over two-thirds of them was uncertain. More detailed data are required to determine the magnitude of the problem and offer possible solutions. Methods: This study examines the finances and use statistics of ct Sew of t hese organizations in more depth, and reviews several economic models that may help sustain them. Results: Six organizations were studied Their administrative overhead is fa irly low; non-administrative personnel and computer related costs account f or 77% of expenses. One smaller, more specialized US database, in 1997, had 60% of total access from US domains; a majority (56%) of its US accesses c ame front commercial domains, although only 2% of the 153 databases origina lly studied received any industrial support. The most popular model used to gain industrial support is asymmetric pricing. preferentially charging the commercial users of a database. At least five biological databases have re cently begun using this model. Advertising is another model which may be us eful for the more general, more heavily used sires. Microcommerce has promi se, especially for databases that do nor attract advertisers, but needs fur ther testing. The least income reported for any of the databases studied wa s $50 000/year; applying this rate to 400 biological databases (a lower lim it of the number of such databases, many of which require far larger resour ces) would mean annual support need of at least $20 million. To obtain this level of support is challenging, yet failure to accept the challenge could be catastrophic.