This paper describes an approach for managing and tracking the variety of information snippets that emerge in the automotive testing domain. The major challenges in this domain include coping with the huge amount of data produced, and, as development cycles shorten while the complexity of systems under development increases, re-using already acquired knowledge. Being able to judge on data relevance requires to keep track of the history of data and under which conditions they evolved. Thus the aspects already covered by workflow systems in the business domain are becoming important in automotive testing as well. Standardization of such workflow systems is driven by the WfMC (Workflow Management Coalition). However, research, development, and testing procedures may need some flexibility to account for unexpected results as well as to perform only partial steps without having to re-define the whole process. This calls for more general methods as they are provided by Petri nets. As data in this domain are heterogeneous and may have respectable size, the ODS (open data services) standard of ASAM (Association for Standardization of Automation and Measuring Systems) is used to store the workflow as well as any related information. The paper bases on some recent investigations in combining these three technologies and takes them one step further by proposing mechanisms for those components treating the dynamic aspects during a workflow run.