This paper presents a planning-based approach for the enu-meration of alternative data-centric workflows specified in ASASEL (Abstract State mAchineS Execution Language), which define the coordination of data and computation services for satisfying data requirements. The optimization of data-centric workflows is associated to the exploration of the parallelization of the workflow activities. We address the exploration of parallelism formalizing the enumeration problem in the DLV-K language. Together, our ASASEL language and enactment engine along with our enumeration approach provide the foundation for a highly flexible mechanism for managing data-centric workflows.