The growth of scientific information and the increasing automation of data collection have made databases integral to many scientific disciplines including life sciences, physics, meteorology, earth and atmospheric sciences, and chemistry. These sciences pose new data management challenges to current database system technologies. The thesis work presented in this paper proposes a database server for next-generation scientific data management. The proposed sever realizes two core requirements in scientific databases, mainly, (1) Annotation management, and (2) Complex dependencies involving human actions. In the paper, we discuss the challenges involved in each of these requirements and present the key contributions and main results in each of the two fronts.