title: Persistence and availability of Web services in computational biology.
abstract: We have conducted a study on the long-term availability of bioinformatics Web services: an observation of 927 Web services published in the annual Nucleic Acids Research Web Server Issues between 2003 and 2009. We found that 72% of Web sites are still available at the published addresses, only 9% of services are completely unavailable. Older addresses often redirect to new pages. We checked the functionality of all available services: for 33%, we could not test functionality because there was no example data or a related problem; 13% were truly no longer working as expected; we could positively confirm functionality only for 45% of all services. Additionally, we conducted a survey among 872 Web Server Issue corresponding authors; 274 replied. 78% of all respondents indicate their services have been developed solely by students and researchers without a permanent position. Consequently, these services are in danger of falling into disrepair after the original developers move to another institution, and indeed, for 24% of services, there is no plan for maintenance, according to the respondents. We introduce a Web service quality scoring system that correlates with the number of citations: services with a high score are cited 1.8 times more often than low-scoring services. We have identified key characteristics that are predictive of a service's survival, providing reviewers, editors, and Web service developers with the means to assess or improve Web services. A Web service conforming to these criteria receives more citations and provides more reliable service for its users. The most effective way of ensuring continued access to a service is a persistent Web address, offered either by the publishing journal, or created on the authors' own initiative, for example at http://bioweb.me. The community would benefit the most from a policy requiring any source code needed to reproduce results to be deposited in a public repository.
authors.affiliation: Machine Learning in Biology Research Group, Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany. sebastian.schultheiss@tue.mpg.de
authors.forename: Sebastian J
authors.initials: SJ
authors.lastname: Schultheiss
authors.forename: Marc-Christian
authors.initials: MC
authors.lastname: Münch
authors.forename: Gergana D
authors.initials: GD
authors.lastname: Andreeva
authors.forename: Gunnar
authors.initials: G
authors.lastname: Rätsch
mesh_terms: D019295:Computational Biology / Q000379:methods / Q000592:standards*; D006801:Humans; D016247:Information Storage and Retrieval / Q000592:standards*; D020407:Internet / Q000592:standards*; D010506:Periodicals as Topic; D015203:Reproducibility of Results