Crop information systems : the next generation

The Generation Challenge Programme (GCP; http://www.generationcp.org) is an international consortium initiated in 2003 and involving international agricultural research centers of the Consultative Group for Agricultural Research (CGIAR; http://www.cgiar.org), several advanced research institutes and a number of developing country national research & extension system (NARES) partners. The GCP's projected 10 year research agenda is directed toward genomics-driven crop improvement for CGIAR crops, using a strategy of comparative biology across crop species, high-throughput molecular characterization of genetic resources diversity for allele mining, and deployment of efficient gene transfer technologies into plant breeding programmes. One key component of consortium activities is a subprogramme focusing on informatics support of GCP germplasm laboratory and field research. The primary goal of this subprogramme (designated Subprogramme 4 or "SP4" for short) is the development of bioinformatics infrastructure and deployment of an integrated crop information platform for the support of genomics-driven plant breeding. The research and development activities of SP4 toward this goal aim at the following elements: - The establishment of a GCP Information Platform. This involves the adoption and/or development of common, public scientific domain models and ontology to cross-link all data types and analysis processes within the program, and the deployment and extension of data templates, web services and registry technologies to capture, share and integrate information across diver-se and globally dispersed data sources. Public software tools will be adopted or newly developed to create an integrated platform of software and databases available as web services. These efforts are documented at http://pantheon.generationcp.org and http://moby.generationcp.org; - The improvement of the GCP Information Platform components. Involving the commissioning of a high performance computational (HPC) grid for high throughput data analyses, the develop-ment of data quality assurance standards for project information including LIMS support; - Creation of software in support of GCP activities. Examples are the development of a catalog and display tools for comparative (plant stress responsive) gene product information, and integration with associated gene expression information, but also the adaptation of existing and development of new plant breeding decision support tools. (Texte integral)