In the context of science, abstract workflows bridge the gap between scientists and technologists towards using computer systems to carry out scientific processes. Provenance traces provide evidence required to validate scientific products and support their secondary use. Assuming abstract workflows and provenance traces are based on formal semantics, a knowledge-based system that consistently merges both technologies allows scientists to document their processes of data collection and transformation; it also allows for secondary users of data to assess scientific processes and resulting data products. This paper presents an evaluation approach for interactions between abstract workflows and provenance traces. The claim is that both technologies should complement each other and align consistently to a scientist's perspective to effectively support science. The evaluation approach uses criteria that are derived from tasks performed by scientists using both technologies.