Implement pipeline between Laboratory Management System and Plant Phenotyping Platform.
In the context of a growing global demand for food and feed the need for improved crop yield and the identification of more efficient as well as better adapted crop plants is an important driving force for high-throughput phenotyping studies which comprise comprehensive and data-intense experiments. The IPK run multiple large-scale plant phenotyping platform including also one of the world-largest plant cultivation halls producing quite a huge amount of plant images. Unfortunately, an integration into the institutional Laboratory Information and Management System (LIMS) is missing. This gap should be closed in frame of this thesis.
The phenotyping platforms as well as the LIMS system basing on a comprehensive relational database management system. The first part would be to identification of the data and files organisation of the PostGreSQL database behind the phenotyping infrastructure and designing a concept for automated linking and transferring the produced information and image files into the institutional LIMS, which is using an Oracle DBMS and a mounted hierarchical storage management system (HSM). Subsequently the major focus of the thesis should be the implementation of a suitable workflow to realize the developed concept. A general experience with relational databases and SQL is essential. Furthermore, programming experience, preferably Java or other related languages are needed. Experience with version control systems (Git, SVN) and Build Management Tools (MVN, Gradle) can be helpful, but is not mandatory.
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If you are interested in this topic, please contact Dr. Daniel Arend for further information.