  Data processing frameworks are an essential part of HEP experiments' software
stacks. Frameworks provide a means by which code developers can undertake the
essential tasks of physics data processing, accessing relevant inputs and
storing their outputs, in a coherent way without needing to know the details of
other domains. Frameworks provide essential core services for developers and
help deliver a configurable working application to the experiments' production
systems. Modern HEP processing frameworks are in the process of adapting to a
new computing landscape dominated by parallel processing and heterogeneity,
which pose many questions regarding enhanced functionality and scaling that
must be faced without compromising the maintainability of the code. In this
paper we identify a program of work that can help further clarify the key
concepts of frameworks for HEP and then spawn R&D activities that can focus the
community's efforts in the most efficient manner to address the challenges of
the upcoming experimental program.
