Albert Schimpf

"Rapid prototyping using declarative specifications for concurrent and composable workflows"

Data science tasks usually involve composing individual tasks to complex workflows and run them in a safe and efficient manner. To help build and understand data-flow heavy tasks, we propose the concept of flows. Flows result by annotating directed graphs with additional arrow types. Arrow types describe data flow, scopes, and concurrency and are used to reason about which parts of the graph are independent from each other. Furthermore, to enable rapid prototyping, a declarative specification is used to build, visualize, and statically type-check a workflow graph. Our work can be used to prototype and run typical data science tasks in an efficient manner.

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