OK here's my idea.

I don't personally think kernelci (or LKFT) are set up to aggregate
results currently. We have too many assumptions about where tests are
coming from, how things are built, etc. In other words, dealing with
noisy data is going to be non-trivial in any existing project.

I would propose aggregating data into something like google's BigQuery.
This has a few benefits:
- Non-opinionated place to hold structured data
- Allows many downstream use-cases
- Managed hosting, and data is publicly available
- Storage is sponsored by google as a part of
  https://cloud.google.com/bigquery/public-data/
- First 1TB of query per 'project' is free, and users pay for more
  queries than that

With storage taken care of, how do we get the data in?

First, we'll need some canonical data structure defined. I would
approach defining the canonical structure in conjunction with the first
few projects that are interested in contributing their results. Each
project will have an ETL pipeline which will extract the test results
from a given project (such as kernelci, lkft, etc), translate it into
the canonical data structure, and load it into the google bigquery
dataset at a regular interval or in real-time. The translation layer is
where things like test names are handled.