Data is one of today’s most important currencies. Thus, maintaining an overview of its creation, usage, and manipulation within an organization is of utmost importance. While this fact has been recognized in the Business Process Management (BPM) community in general, leading to the emergence of disciplines such as process mining, its subfield of process modeling has not attributed attention to that for a long time. BPM is a mature methodology whose objective it is to systematically model, analyze, optimize, and enact business processes. One of the central concepts in BPM are process models, i.e., representations of the different steps the various actors in an organization undertake to achieve the business goals. Extensive research has been conducted on the logical and temporal order of these steps, also called the control flow, specifically on how to visualize and analyze them. While doing so, the impact of data on control flow, e.g., that certain tasks require specific data to be executed, has been largely neglected. Even with the extension of some of the process modeling languages to incorporate data concepts, formal semantics of these concepts that enable automated analysis and enactment are often not present or underspecified. This thesis approaches this gap by introducing a concise semantics for data concepts in BPMN, one of the most widely used process modeling languages in academia and industry. As a first step, a missing notation for some of these data concepts is introduced. The assignment of formal semantics then happens through a mapping of BPMN concepts to Petri nets, a well-understood language with exact execution semantics. The resulting models’ behavior is compared to the BPMN specification to ensure a correct mapping. Based on the defined formalism, analysis methods are presented to verify the correctness of the data flow of BPMN models. That includes the soundness criterion as well as the detection of anti-patterns that indicate erroneous and undesired behavior, and data output analysis, which supports compliance and consistency checks.