I'm reviewing SciSpace for my team's literature management. I've hit a blocker right away.
I uploaded a batch of PDFs, but the author names parsed incorrectly. I need to fix about 50 entries. The article edit screen only lets me correct authors one paper at a time, which is painfully slow. Is there really no way to bulk edit author metadata? Maybe a hidden import/update feature or a workaround using the CSV export?
I don't see anything in the docs. This seems like a basic feature for any research tool. How are others handling this?
Yeah, that CSV export is your best bet, but it's not a direct fix. I've done this dance.
> Maybe a workaround using the CSV export?
You can export your library to CSV, edit the author column in a spreadsheet, and then re-import. The catch? SciSpace will likely treat the import as *new* entries, creating duplicates. You'll have to delete the originals after, which is its own headache.
If they have an API, you could script the updates, but that's a whole project. For 50 entries, the CSV delete-and-reimport might still be faster than one-by-one, sadly. Their metadata handling really should be better.
it's always an API issue
That CSV export/reimport is the only real option, but user145 is right about the duplicates. It's a terrible user experience.
Check if the export includes unique IDs. If it does, and the import process respects them for updates, you've got a path. If not, you're stuck with delete/reimport, which makes it barely faster than manual fixes.
Honestly, for a research tool, missing bulk edit is a major red flag. It shows they didn't think about actual workflows. I'd reconsider the tool choice if this is a dealbreaker.
The CSV export/reimport is the official workaround, but it has a critical flaw they don't advertise. The export doesn't include a mutable unique key for updates, only an internal ID. Even if you edit the author field and reimport, the system will create duplicates as noted.
I've had to do this for a client. The fastest method is actually a hybrid: use the CSV as your editing worksheet, then manually apply changes using keyboard shortcuts in the UI. Open each article in a new tab from your corrected list, tab to the author field, paste, save, close. It's still manual but avoids the deduplication nightmare. For 50 entries, that's maybe 15 minutes of focused work.
It's a clear oversight in their data model. If this is a recurring need, you should build a small script against their API, though that requires dev time.
Mike
Your hybrid approach of using the CSV as a reference sheet for manual editing is clever, and it correctly sidesteps the data model's core issue: the lack of a proper external ID for mutation.
The observation about the internal ID is key. It implies their data layer treats create and update as distinct operations, with no upsert mechanism exposed. This is a common architectural smell when the backend is built as a simple CRUD layer over a database, without considering batch operations as a first-class use case.
If you were to script against the API, you'd still face that same mutation problem unless they offer a PATCH endpoint for individual records, which would still require iterating through each item ID. The real missing feature is a bulk PATCH operation, but that's rarely implemented without significant demand.
Good catch on the architectural smell. That lack of an upsert is exactly what makes the CSV a dead-end for updates. If you're scripting, you're stuck looping through individual PATCH calls anyway, so you might as well use the CSV just to generate the API payloads.
I'd check if the internal ID from the export is even the same ID the API expects. Sometimes they're different, which adds another layer of frustration.
Data is the new oil - but it's usually crude.