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Bioinformatics Advance Access published online on December 21, 2004

Bioinformatics, doi:10.1093/bioinformatics/bti234
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Bioinformatics © Oxford University Press 2004; all rights reserved.
Received October 19, 2004
Revised December 15, 2004
Accepted December 15, 2004

Article

A framework for scientific data modeling and automated software development

Rasmus H. Fogh 1, Wayne Boucher 1, Wim F. Vranken 2, Anne Pajon 2, Tim J. Stevens 1, T. N. Bhat 3, John Westbrook 4, John M. C. Ionides 2*, and Ernest D. Laue 1

1 Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK
2 MSD group, EMBL-EBI, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
3 Biotechnology Division (831), NIST, 100 Bureau Drive, Stop 8310, Gaithersburg, MD 20899-8314, USA
4 Department of Chemistry and Chemical Biology, Rutgers University, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854- 087, USA

* To whom correspondence should be addressed.
John M. C. Ionides, E-mail: ccpn{at}mole.bio.cam.ac.uk


   Abstract

Motivation: The lack of standards for storage and exchange of data is a serious hindrance for the large-scale data deposition, data mining and program interoperability that is becoming increasingly important in bioinformatics. The problem lies not only in defining and maintaining the standards, but also in convincing scientists and application programmers with a wide variety of backgrounds and interests to adhere to them.

Results: We present a UML-based programming framework for the modeling of data and the automated production of software to manipulate that data. Our approach allows one to make an abstract description of the structure of the data used in a particular scientific field and then use it to generate fully functional computer code for data access and input/output routines for data storage, together with the accompanying documentation. This code can be generated simultaneously for different programming languages from a single model, together with the format descriptions and I/O libraries for, e.g. XML and various relational databases. The framework is entirely general and could be applied in any subject area. We have used this approach to generate a data exchange standard for structural biology and analysis software for macromolecular NMR spectroscopy.

Availability: The framework is available under the GPL license, the data exchange standard with generated subroutine libraries under the LGPL license. Both may be found at {{http://www.ccpn.ac.uk}}.

Supplementary information: A more detailed description of the CCPN data model and the generated Python API has been deposited with the article.


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