I have recently added a page on Terminology to my RecursiveExhaustion.com site, but I must clear up something more fundamental first. Data Science and Data Technology are not the same thing. Even the book called Data Science in the MIT Press Essential Knowledge series gets this wrong from the start. Not to be pedantic, but Science, Technology, and Engineering are different things.
We all know that science is the empirical or deductive search for knowledge, as in physics or mathematics. During scientific endeavor some basic technologies may emerge, but these are not science by themselves. Technology is the study and collection of tools and techniques. Engineering is the application of technology. Technologists learned the tools and techniques of working with iron before engineers built bridges with it.
OK, this is pretty pedantic. Sorry about that. But as I said, even books from MIT get it wrong. Their book, supposedly on Data Science, is clearly about Data Technology, and much of it about Data Engineering. Read it and see for yourself. More than anything it is about applications.
The first attempts to model the human nervous system with artificial neural networks were scientific. The early explorations of them as possible tools was technology, and their deployment in large scale systems for biometric user authentication is engineering.
Again, please see Terminology and other pages on my Recursive Exhaustion Sitemap for an example of the way I use these terms. Most of that terminology is an illegitimate combination of standard usage in these disciplines and my own, which evolved over many long years of work on my own projects, such as my mildly crazy Acronymic Language project.