Comment by westurner
There are processes and business processes around knowledge graphs like there are for any other dataset.
OTOH; ETL, Data Validation, Publishing and Hosting of dataset and/or servicing arbitrary queries and/or cost-estimable parametric [windowed] reports, Recall and retraction traceability
DVC.org and the UC BIDS Computational Inference notebook book probably have a better enumeration of processes for data quality in data science.
...
With RDF - though it's a question of database approach and not data representation -
Should an application create a named graph per database transaction changeset or should all of that data provenance metadata be relegated to a database journal that can't be read from or written to by the app?
How much transaction authentication metadata should an app be trusted to write?
A typical SQL webapp has one database user which can read or write to any column of any table.
Blockchains and e.g. Accumulo require each user to "connect to" the database with a unique key.
It is far harder for users to impersonate other users in database systems that require a cryptographic key per user than it is to just write in a different username and date using the one db cred granted to all application instances.
W3C DIDs are cryptographic keys (as RDF with schema) that can be generated by users locally or generated centrally; similar to e.g. Bitcoin account address double hashes.
Users can cryptographically sign JSON-LD, YAML-LD, RDFa, and any other RDF format with W3C DIDs; in order to assure data integrity.
How do data integrity and data provenance affect the costs, utility, and risks of knowledge graphs?
Compared to GPG signing git commits to markdown+YAML-LD flat files in a git repo, and paying e.g gh to enforce codeowner permissions on files and directories in the repo by preventing unsigned and unauthorized commits, what are the risks of trusting all of the data from all of the users that could ever write to a knowledge graph?
Which initial graph schema support inference and reasoning; graph rewriting?