I'm beginning to suspect that it could be relevant soon. If you wait for such advanced AI that can understand your documentation, you're making it harder than it has to be, kinda like Marcus is saying in OP. You could solve this with just tons of raw data, but that seems unnecessarily hard. For a firm with the usual small dataset, maybe even unrealistically hard.

Anyways, with some naive googling I found these references which seem interesting with regards to lineage and causality (for the query "lineage causal database schema"):

[0] Causality and Explanations in Databases. The "Related topics in Databases" section seems interesting.

[1] Duke's 'Understanding Data: Theory and Applications, Lecture 16: Causality in Databases' (by one of [0]'s authors).

[2] Quantifying Causal Effects on Query Answering in Databases. This has some interesting definitions.

[3] Causality in Databases. Seems like a more in depth version of [0].

[4] A whole course on "Provenance and lineage"

[5] Causality and the Semantics of Provenance. Defines "provenance graphs" and some properties.

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[0] http://www.vldb.org/pvldb/vol7/p1715-meliou.pdf

[1] https://www2.cs.duke.edu/courses/fall15/compsci590.6/Lecture...

[2] https://www.usenix.org/sites/default/files/conference/protec...

[3] https://www.cs.cornell.edu/home/halpern/papers/DE_Bulletin20...

[4] https://cse.buffalo.edu/~chomicki/cse703-s18.html

[5] https://arxiv.org/pdf/1006.1429.pdf