Abstract : An increasing number of scientific experiments are"in-silico": carried out at least partially using computers. Scientific Workflows have become a key tool to model and implement such experiments, but they tangle domain knowledge, tech- nical know-how and non-functional concerns and are, as a result, difficult to understand, reuse or repurpose. In order to ease Scientific Workflow Reuse, this paper de- fines a Conceptual Workflow model that is closer to the end- user's domain and intentions. By placing our model higher on the abstraction scale, we can separate concerns and em- phasize the in-silico experiment inside the workflow, thus improving readability and re-usability. The conceptual representation can then be transformed into a regular Abstract Scientific Workflow, exploiting both domain and non-functional knowledge that are captured and harnessed through the use of Semantic Web technologies.