  Today, many industrial processes are undergoing digital transformation, which
often requires the integration of well-understood domain models and
state-of-the-art machine learning technology in business processes. However,
requirements elicitation and design decision making about when, where and how
to embed various domain models and end-to-end machine learning techniques
properly into a given business workflow requires further exploration. This
paper aims to provide an overview of the requirements engineering process for
machine learning applications in terms of cross domain collaborations. We first
review the literature on requirements engineering for machine learning, and
then go through the collaborative requirements analysis process step-by-step.
An example case of industrial data-driven intelligence applications is also
discussed in relation to the aforementioned steps.
