Project Z2 of CRC ReceptorLight: Integrative Data Management and Processing


Startdate: 2015-11-01

Status: active

Member:
Birgitta König-Ries
Sheeba Samuel
Prof. Dr.-Ing. Hanns Martin Bücker (Advanced Computing)
Dipl.-Kfm. Andreas Henkel (Information Technology Group, Jena University Hospital)
Dipl.-Inf. Frank Taubert (Advanced Computing)
Dipl.-Ing. Daniel Walther (Advanced Computing)

Description

Project Z2 of CRC ReceptorLight is jointly carried out by the Jena University Hospital and Friedrich Schiller University Jena within the framework of the Collaborative Research Centre (CRC) “High-end light microscopy elucidates membrane receptor function (Receptor Light)” established in 2015. CRC ReceptorLight is funded by the German Research Foundation (DFG) and consists of around 20 research projects from various institutions located in Jena and Würzburg. It will apply and develop light microscopy techniques with highest resolutions in space and time. The volume of the resulting datasets will be large, expected to be in multi-petabyte data.
The overall goal of project Z2 is to provide a knowledge management, sharing and processing platform that will enable the CRC to sustainably store data, to efficiently access and process data as well as to explore new, integrative, and reproducible methods for knowledge generation from data. Such a platform will not only be beneficial to the researchers, but also crucial for communication of data and knowledge across different projects. The platform should guarantee high reliability and scalability to a large amount of heterogeneous data.
The aim of the project in the first phase (2015-2019) are:
1. The design and implementation of a data storage concept guaranteeing high reliability and scalability to a large amount of data.
2. The design and implementation of a meta database that stores information describing the acquisition, quality, provenance, and interpretation of data. This includes linking to
the actual data and processes.
3. The design and implementation of a collaborative platform as part of a virtual research environment that enables the efficient analysis across the locations and the participating institutions.