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Comparative and Functional Genomics
Volume 5, Issue 2, Pages 184-189
Conference review

The PlaNet Consortium: A Network of European Plant Databases Connecting Plant Genome Data in an Integrated Biological Knowledge Resource

1Technische Universität München, Chair of Genome-oriented Bioinformatics, Center of Life and Food Science, Freising-Weihenstephan D-85350, Germany
2Institute for Bioinformatics (MIPS), GSF National Research Centre for Environment and Health, Ingolstäedter Landstraße 1, Neuherberg D-85764, Germany

Received 13 November 2003; Accepted 24 November 2003

Copyright © 2004 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The completion of the Arabidopsis genome and the large collections of other plant sequences generated in recent years have sparked extensive functional genomics efforts. However, the utilization of this data is inefficient, as data sources are distributed and heterogeneous and efforts at data integration are lagging behind. PlaNet aims to overcome the limitations of individual efforts as well as the limitations of heterogeneous, independent data collections. PlaNet is a distributed effort among European bioinformatics groups and plant molecular biologists to establish a comprehensive integrated database in a collaborative network. Objectives are the implementation of infrastructure and data sources to capture plant genomic information into a comprehensive, integrated platform. This will facilitate the systematic exploration of Arabidopsis and other plants. New methods for data exchange, database integration and access are being developed to create a highly integrated, federated data resource for research. The connection between the individual resources is realized with BioMOBY. BioMOBY provides an architecture for the discovery and distribution of biological data through web services. While knowledge is centralized, data is maintained at its primary source without a need for warehousing. To standardize nomenclature and data representation, ontologies and generic data models are defined in interaction with the relevant communities.Minimal data models should make it simple to allow broad integration, while inheritance allows detail and depth to be added to more complex data objects without losing integration. To allow expert annotation and keep databases curated, local and remote annotation interfaces are provided. Easy and direct access to all data is key to the project.