My first exposure to data flow as an IT design paradigm came around 1983/4 in the form of Myers and Constantine's work on "Structured Design" which dates from 1974.
I remember at the time finding the idea really appealing but yet, the forces at work in the industry and in academic research pulled mainstream IT design towards non-flow-centric paradigms. Examples include Stepwise Decomposition/Structured Programming (e.g Dijkstra), Object Oriented Design e.g. (Booch), Relational Data modelling (e.g. Codd).
Over the years, I have seen pockets of mainstream IT design terms emerging that have data flow-like ideas in them. Some recent relevant terms would be Complex Event Processing and stream processing.
Many key dataflow ideas are built into Unix. Yet creating designs leveraging line-oriented data formats, piped through software components, local-and-remote, everything from good old 'cat' to GNU Parallels and everything in between, has never, to my knowledge, been given a design name reflective of just how incredibly powerful and commonplace it is.
Things are changing I believe, thanks to cloud computing and multi-core parallel computing in general. Amazon AWS pipeline, Google Dataflow, Google Tensorflow are good examples. Also, bubbling away under the radar are things like FBP (Flow Based Programming), buzz around Elixer and similar such as shared-nothing architectures.
A single phrase is likely to emerge soon I think. Many "grey beards" from JSD (Jackson Stuctured Design), to IBM MQSeries (asynch messaging), to Ericsson's AXE-10 Erlang engineers, to Unix pipeline fans, will do some head-scratching of the "Hey, we were doing this 30 years ago!" variety.
So it goes.
Personally, I am very excited to see dataflow re-emerge to mainstream. I naturally lean towards thinking in terms of dataflow anyway. I can only benefit from all the cool new tools/techniques that come with mainstreaming of any IT concept.