17. April 2019 · Lena Wiese (Georg-August-Univeristät Göttingen) · Flexible and Secure Management of Biomedical Data

Wiese

Flexible and Secure Management of Biomedical Data


Due to the ongoing progress of the digital transformation of research and science, large bodies of data (so-called big data) have to be analyzed with the support of novel data management technologies for
example in personalized medicine. Moreover – for sake of reproducibility and validation of research results (for example in clinical studies) – research data should gradually be transferred into repositories that make the raw data accessible to other researchers (so-called open data). These repositories also allow to connect several independent data sets (so-called deep data) to produce previously impossible scientific insights in the individual disciplines (like better personalized health predictions) or even across disciplines. To provide efficient access to data, novel services are required comprising enhanced data storage, management and analysis technology. As a special application domain, in the Life Sciences there is a growing demand to process increasing amounts of biological and medical data; for
these data, additional concerns arise with respect to data protection because secure management of patient-related data has to be ensured. In this talk I will discuss several approaches to enable efficient and security-enhanced data analysis in health applications.