title: Financing a future for public biological data.
abstract: BACKGROUND
  The public web-based biological database infrastructure is a source 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. An earlier study of 153 biological databases (Ellis and Kalumbi, Nature Biotechnol., 16, 1323-1324, 1998) determined that 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 a few of these organizations in more depth, and reviews several economic models that may help sustain them.
  
  
  RESULTS
  Six organizations were studied. Their administrative overhead is fairly low; non-administrative personnel and computer-related costs account for 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 came from commercial domains, although only 2% of the 153 databases originally 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 recently begun using this model. Advertising is another model which may be useful for the more general, more heavily used sites. Microcommerce has promise, especially for databases that do not attract advertisers, but needs further testing. The least income reported for any of the databases studied was $50,000/year; applying this rate to 400 biological databases (a lower limit of the number of such databases, many of which require far larger resources) 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.
  
  
  BACKGROUND
  lynda@tc.umn. edu
authors.affiliation: Department of Laboratory Medicine and Pathology and Department of Applied Economics, University of Minnesota, Minneapolis, MN 55455, USA.
authors.forename: L B
authors.initials: LB
authors.lastname: Ellis
authors.forename: D
authors.initials: D
authors.lastname: Kalumbi
mesh_terms: D019295:Computational Biology / Q000191:economics* / Q000639:trends; D016208:Databases, Factual / Q000191:economics*; D005378:Financial Support; D020407:Internet / Q000191:economics* / Q000458:organization & administration; D018803:Models, Economic