Central project Z2: Data management
Integrated data management and synthesis
PI: Christian Wirth, Dr. (MPI Jena)
Co-PI: Jens Schumacher, Dr. (Uni Jena)
Summary
The mere size of the project, the sophistication of the experimental design, the large number of closely linked subprojects and not least the need for fast and efficient data exchange between German and Chinese researchers make an integrated web-based data management indispensable. The three main goals of this subproject are (1) to develop a project database specifically tailored to reflect the main scientific questions and the experimental design, (2) to provide statistical tools for the common analysis and synthesis of the project data and (3) to lead the acquisition and analysis of trait data from the literature for a regional up-scaling of the experimental results using the functionalities of the FET database. All aspects of this work will be done in close collaboration with the Chinese counterparts Kequan Pei, Mei Yu and Dayong Zhang, who will be responsible for the GIS-component of the data management. The joint data management project will further guide the process of developing data standards and sampling protocols and will test data acquisition tools for use in the field. Throughout the lifetime of the project, the data management will perform the maintenance of the database which includes quality control of incoming data and dissemination of data to project members and to the public.
Objectives
The database proposed here will meet all requirements of a multi-user project database accommodating heterogeneous data. It will also be linked to a Geographical Information System and it will contain elements of a trait database. In summary, this subproject has the following objectives:
1. Develop a database specifically tailored to reflect the main scientific questions and the experimental design
2. Support the measurement activities with data acquisition tools
3. Organise the development of data standards and protocols
4. Provide a database for and conduct assimilation of trait data from the literature
5. Organise data exchange within and between the research groups
6. Support the data analysis by providing a range of statistical tools
7. Disseminate the data to the public