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This is a "planing" issue on adding metadata extraction and "storage" within registry to formalize what we are to develop in immediate next steps (placing details of "metadata usage" such as search aside, but keeping them in mind).
Metadata extraction per dataset should be done using WiP https://github.com/datalad/datalad-metalad which is a replacement for "built-in" in current DataLad metadata interfaces/storage approach
"autodeducting" extractors should be added (datasets will likely be not configured for specific extractor) based on the data found in a dataset
probably will care to extract only for repositories which are datalad datasets (i.e have non-None .id)
not yet sure 100% if seamless FUSE access would be possible or we might need to make metalad extractors become "streaming backend aware" (may be in the now https://github.com/datalad/datalad-deprecated/ `datalad.auto fashion, at least for the pure-in-Python extractors
administrative interfaces to clean up cached data might be needed
Introduce to registry tracking of subdatasets
ATM all datasets in the registry are "independent"
we need to add many-to-many "subdatasets" table which would establish relationships between dataset/version's
figure out how to provide metadata extractors with a "super-dataset" view when needed
This is a "planing" issue on adding metadata extraction and "storage" within registry to formalize what we are to develop in immediate next steps (placing details of "metadata usage" such as search aside, but keeping them in mind).
.id
)Attn @jwodder and @datalad/developers on what other high level components or related aspects you see I have missed or have ideas about.
Attn @jwodder and @datalad/developers on what other high level components or related aspects you see I have missed or have ideas about.
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