The challenge of digital preservation of scientific data lies in the need to preserve not only the dataset itself but also the ability it has to deliver knowledge to a future user community. A true scientific research asset allows future users to reanalyze the data within new contexts. Thus, in order to carry out meaningful preservation we need to ensure that future users are equipped with the necessary information to re-use the data. This paper presents an overview of a preservation analysis methodology which was developed in response to that need on the CASPAR and Digital Curation Centre SCARP projects. We intend to place it in relation to other digital preservation practices, discussing how they can interact to provide archives caring for scientific data sets with the full arsenal of tools and techniques necessary to rise to this challenge.