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This is a discussion regarding my OpenRefine experience so far (mostly for @maregold to prepare for the presentation). Feel free to add more if you've worked with OpenRefine and have similar or other issues. I'll add more to this down the comments as we go.
Quirks/Struggles
Doesn’t handle nested structures like json too well
OpenRefine forum has a discussion on this that summarizes my experience pretty well, namely how they don’t support hierarchical structures with depth greater than 1
So for databases like MusicBrainz where we have structured json-ld exports, we have to be smart and tedious about it
Still don’t understand their json-ld handling: They have support for it but can’t even handle nested json-ld structures
Limited Scripting support: I want to utilize OpenRefine reconciliation power within a script to enhance automation but has no native support for that. Just found softwares called openrefine-batch OR orcli (OpenRefine command-line interface) that deal with this but we’ll see
Doesn’t support reconciliation for column name (This is a bit specific to our needs so I don’t think its their fault)
Things I really like
Ability to export configs and reconciliation decisions and reapply them for datasets of similar schema
Reconciliation process relatively straightforward and easy. Reconciliation decisions for cell values are recorded for future reconciliation
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This is a discussion regarding my OpenRefine experience so far (mostly for @maregold to prepare for the presentation). Feel free to add more if you've worked with OpenRefine and have similar or other issues. I'll add more to this down the comments as we go.
Quirks/Struggles
OpenRefine forum has a discussion on this that summarizes my experience pretty well, namely how they don’t support hierarchical structures with depth greater than 1
https://forum.openrefine.org/t/representing-hierarchical-data-beyond-the-records-mode/425
So for databases like MusicBrainz where we have structured json-ld exports, we have to be smart and tedious about it
Things I really like
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