Data play a central role in most fields of science. In recent years, the amount of data from experiment, observation, and simulation has increased rapidly and data complexity has grown. Also, communities and shared storage have become geographically more distributed. Therefore, methods and techniques applied to scientific data need to be revised and partially be replaced, while keeping the community-specific needs in focus. The German Helmholtz Association project "Large Scale Data Management and Analysis" (LSDMA) aims to maximize the efficiency of data life cycles in different research areas, ranging from high energy physics to systems biology. In its five Data Life Cycle Labs (DLCLs), data experts closely collaborate with the communities in joint research and development to optimize the respective data life cycle. In addition, the Data Services Integration Team (DSIT) provides data analysis tools and services which are common to several DLCLs. This paper describes the various activities within LSDMA and focuses on the work performed in the DLCLs.