There's a lot of this kind of scientization of history going around, and while I don't have time to say everything I might want to, I do have a couple of thoughts. https://www.theguardian.com/technology/2019/nov/12/history-as-a-giant-data-set-how-analysing-the-past-could-help-save-the-future?CMP=share_btn_tw

1. At least this story actually quoted some historians. It's surprisingly common for stories pumping big data to bother. So, kudos on interviewing people directly involved in the subject of the piece.

2. History is not a data set. History is a discipline.

History may supply data. But phrases like "history is a massive data set" are a huge part of why so many historians see this kind of work as shallow crap.

3. The idea that "history is a massive data set" is a huge part of why some of these exercises *are* shallow crap, because -- though it needn't -- it is often taken to imply that handling data is the same as doing history. And that anything else historians do is extraneous.

4. Treating a discipline like a data buffet is bad for the discipline, bad for those who practice it, and bad for the institutions that house it. It is similar in this respect to treating history as merely a source of transferable skills. All real expertise can be got elsewhere.

5. The fact that simple data can be extracted (or extrapolated) from complex and partial historical sources does not make those sources simpler or more complete. The fact that mathematical formulas can be derived from such data does not make those formulas true.

6. Sooner or later the fact that our knowledge of the past rests ultimately on sources, not data, is going to catch up with any attempt to make history a predictive science.

Or so I predict.

7. Inspired by my friend and sometime collaborator Vera Keller (read her book), here are some desiderata for improving these discussions

- an account of "data"
- an account of historical process
- an exhaustive causal account of a major historical event
- all the missing sources

- a theoretical and historical account of the relationship between "using big data" and "seeing the big picture"
- an account of the epistemic value of machine and computing metaphors
- a complete map of the world outside big data