Data management pipeline for plant phenotyping in a multisite project
Kenny Billiau A , Heike Sprenger A , Christian Schudoma A , Dirk Walther A and Karin I. Köhl A B
+ Author Affiliations
- Author Affiliations
A Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, 14476 Potsdam OT Golm, Germany.
B Corresponding author. Email: koehl@mpimp-golm.mpg.de
Functional Plant Biology 39(11) 948-957 https://doi.org/10.1071/FP12009
Submitted: 13 January 2012 Accepted: 22 June 2012 Published: 15 August 2012
Journal Compilation © CSIRO Publishing 2012 Open Access CC BY-NC-ND
Abstract
In plant breeding, plants have to be characterised precisely, consistently and rapidly by different people at several field sites within defined time spans. For a meaningful data evaluation and statistical analysis, standardised data storage is required. Data access must be provided on a long-term basis and be independent of organisational barriers without endangering data integrity or intellectual property rights. We discuss the associated technical challenges and demonstrate adequate solutions exemplified in a data management pipeline for a project to identify markers for drought tolerance in potato. This project involves 11 groups from academia and breeding companies, 11 sites and four analytical platforms. Our data warehouse concept combines central data storage in databases and a file server and integrates existing and specialised database solutions for particular data types with new, project-specific databases. The strict use of controlled vocabularies and the application of web-access technologies proved vital to the successful data exchange between diverse institutes and data management concepts and infrastructures. By presenting our data management system and making the software available, we aim to support related phenotyping projects.
Additional keywords: controlled vocabulary, data integration, field trials, marker assisted selection, mixed schema design, ontologies.
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