Information systems, developed for several economic segments, increasingly demand data traceability functionality. To endow information systems with such capacity, we depend on data provenance modeling. Provenance enables legal compliance, experiment validation, and quality control, among others . Provenance also helps identifying participants (determinants or immanents) like people, organizations, software agents among others, as well as their association with activities, events or processes. It can also be used to establish levels of trust for data transformations. This dissertation proposes a generic conceptual model for provenance, designed by aligning fragments of upper ontologies, international standards and broadly recognized projects. The contributions are in two directions: a provenance conceptual model - extensively documented - that facilitates interoperability and the application of a design methodology based on ontology alignment.