Reproducibility of results is a key element for the verification of scientific experiments and an important indicator of the quality of a published experiment. It is vital therefore to precisely and transparently share both the method and the data associated with an experiment. Data associated with an experiment is often linked within peer-reviewed sci- entific publications, and is difficult to assess in a consistent manner. In this paper we explore how emerging linked data standards can be applied to the description and data of pub- lished adaptivity and personalisation experiments in a man- ner that can be linked from publications and easily located, accessed and reused to repeat an experiment. The approach also provides possibilities for published experiments to be extended or modified to provide a firmer grounding for pub- lishing new results and conclusions.