This work intends to provide a data management solution based on the concepts of dataspaces for the large-scale and long-term management of scientific data. Our approach is to semantically enrich the existing relationship among primary and derived data items, and to preserve both relationships and data together within a dataspace to be reused by owners and others. To enable reuse, data must be well preserved. Preservation of scientific data can best be established if the full life cycle of data is addressed. This is challenged by the e-Science life cycle ontology, whose major goal is to trace the semantics about procedures in scientific experiments. We present a theoretical dataspace model for e-Science applications, its implementation within a dataspace support platform and an experimental evaluation on top of two real world application domains.