Data flow in a workflow refers to the movement of data between its constituent tasks. Specifically, it is the process where the output generated by one task is passed on to become the input for one or more subsequent tasks. This mechanism allows for a chain of operations to be performed on a dataset, with each task contributing to the progressive transformation or analysis of the data. It is a fundamental concept that distinguishes data-centric workflows from purely control-flow-driven processes.

A. Transitioning between tasks: This describes control flow, which dictates the order and conditions under which tasks are executed, not the movement of data itself.

C. Dependency graph of tasks: A dependency graph visually represents the control flow and dependencies, showing which tasks must complete before others can start, but it is not the data flow itself.

D. Defines operation to perform: This describes the function of an individual task or node within the workflow, not the mechanism for passing data between different tasks.

---

1. Official Vendor Documentation (Nokia): In the context of Nokia's Network Services Platform (NSP), workflows are used for network automation. The documentation explains that a key feature is the ability to "chain a set of tasks together, where the output of one task can be used as the input to another." This directly describes the process of passing data between tasks.

Source: Nokia Network Services Platform (NSP) Workflow Manager Guide, Release 21.11, Section: "Workflow overview".

2. University Courseware: University courses on distributed systems and data processing define dataflow programming models as graphs where nodes are computational tasks and edges represent the data paths between them. The model's focus is on how data is passed and transformed through the graph.

Source: Matei Zaharia, "CS245: Principles of Data-Intensive Systems," Stanford University, Winter 2021, Lecture 2: "Dataflow Models," Slides 5-8.

3. Peer-Reviewed Academic Publication: Foundational literature on workflow management systems formally defines a workflow as a graph of tasks. The data flow aspect is characterized by the data links or channels that connect tasks, enabling the transfer of data products from a producer task to a consumer task.

Source: Deelman, E., Gannon, D., Shields, M., & Taylor, I. (2009). "Workflows and e-Science: An overview of workflow system features and capabilities." Future Generation Computer Systems, 25(5), 528-540. https://doi.org/10.1016/j.future.2008.06.012 (See Section 2.1, "Workflow Concepts and Components").