Data integration in life sciences

摘要

Big Data Analytics is one of the big buzzwords in the life sciences. Particularly in medicine expectations are high, considering future Learning Health Systems and Precision Medicine approaches. Nevertheless it is often undervalued, that data heterogeneity (variability) is one of the major aspects of big data and that integration of various types of data from extremely heterogeneous original data sources is therefore also one of the major obstacles towards efficient big data analytics. Research on data integration has already brought up a large spectrum of supporting tools that are helpful for a better understanding of heterogeneous sources, ease extraction and transformation tasks, and enable the specification of processing pipelines for ad hoc aggregation of large volumes of data. However, it has also become clear that the ambitious goals in healthcare require both, interdisciplinary cooperation among researchers, and different healthcare institutions to cooperate and share their data across institutional borders.