PI's: Prof. Dr. Alfons Kemper, Prof. Dr. Klaus A. Kuhn    
PhD student: Bernd Vögele, Dipl. Wi-Inf.; Dominik Schmelcher, Dipl. Inf. (associated)

Data integration is playing a major role in medical research, especially when genotype and phenotype associations are being investigated, and when clinical trial data, bio-banks, image data and the results of 'omics' analyses (genomics, proteomics, metabolomics, etc.) have to be managed. Intra-, inter-institutional and international collaboration is necessary in order to gain sufficient power for statistical analyses and for a broader picture of co-morbidities. In this context, complex collaborative processes have to be supported by information technology, and concepts are needed to support cooperation and to manage distribution, heterogeneity and complexity. Research data have to fulfill high quality standards based on well defined, to some degree formalized processes for generation, capture, and management of data.

Consistent approaches to annotation, documentation of provenance, and usage of metadata are needed. The process of translating results from bench to bedside and back is highly complex, multifaceted, and in constant need of integrating newly developed methods and technology platforms. Projects like BRIDG indicate that there is a lack of shared understanding of semantics of medical research. Typically, separate information systems are used for clinical documentation and for clinical trial data management which have evolved separately in clinical and in research environments. Often, within one organization, similar data are entered multiple times, different identifiers are used, and the semantics of similar data items in different systems is not controlled by a common vocabulary.

The idea of reducing complexity, and, e.g., accessing clinical data repositories and registers for research purposes is obvious, but legal constraints have to be observed, pseudonymization concepts are needed, and use cases have to be chosen carefully. As translational research processes are not sufficiently supported by information technology, concepts, tools, and systems have been developed by a number of large-scale initiatives. CaBIG is aiming at the development of a network of tools, data, and researchers in order to support translational and clinical research in oncology. MIMM, the Molecular Medicine Informatics Model is a ?virtual? research repository of clinical, laboratory and genetic data sets. The RFD profile of IHE/CDISC is addressing the question of using point-of-care data capture for both the medical record and clinical research in the setting of a clinical trial.