Welcome to the HUMIT-Project

Analyses in biomedical high-throughput research require extensive integration of heterogeneous data sources (experiments, archives, specialized databases). Existing tools for data integration and analysis of biomedical data are not sufficiently flexible and expressive, because issues and data sources are continuously evolving, and information must be semantically interpreted and adapted by users.

A Big Data approach will have a significant positive effect on the research and development capability of Germany in the Life Sciences, by enabling scientists to control and evaluate cross- domain analysis of high-throughput experiments better than previously possible. The value of the collected data will substantially increase, and at the same time, the potential of the high-throughput research will increase in order to identify causes of disease and to find the right therapies.

The main themes of the proposed approach are an incremental approach to the definition of data models and integration rules as well as the separation of raw data storage of the data preparation for analysis. The interaction will be integrated with the user as a key element in the data processing process. The application of the project results in a service scenario or marketing of individual components is provided due to the high demand for big data solutions in the Life Sciences.