datahub VS grobid

Sounds like you are looking for a data catalog tool instead of db schema management tool. You can check out Amundsen (https://www.amundsen.io/), DataHub (https://datahubproject.io/)

If you are looking for schema change management tool, then you can check out Bytebase (bytebase.com). But it can't answer questions like "which collections contain links to bigmongo.user.id?"

IIUC DataHub (open source project out of LinkedIn) might be relevant here

I’m a huge fan of DataHub, the open source data catalogue spun out of LinkedIn, but it’s best thought of as an observability layer for data assets that can be shared by data engineers and analyst-types. For data users: it’s a stellar search/discovery interface (what datasets are there on this keyword, which are most broadly used across the organization, what downstream products are made with this data, what’s it usually joined to, are it’s upstream pipelines reliable). For data engineers, it’s a comprehensive asset cataloger, crawling your warehouse, orchestrator, modeling layers, features, and reports, matching the lineage into a graph where it can.

If you are looking for a data cataloguing solution, look at Datahub. Haven't used it, but heard good things about it.

What I am looking for is a solution (similar to Amundsen or [Datahub](https://datahubproject.io/)) that also allows to add tables and their metadata manually.

Hello everyone, I'm looking for an open-source data lineage app (e.g. tokern, datahubproject, openmetadata).

What about DataHub? Haven't really used it but I'm actively reading about it and about to use it for some light documentation for some small pipelines.

Interesting concept. Grobid tries to do the same https://github.com/kermitt2/grobid

I would suggest using grobid - a pipeline for extracting scientific PDFs into a common XML format which can be easily parsed. Grobid has quite a nice mature REST API that I've used in some of my own projects. It parses references and matches them to their DOI using the CrossRef API with a reported 95% F1 score. This should make your job pretty simple as far as I can tell - all you'd need to do is run your papers through grobid and then build a citation graph by comparing document DOIs.

Just use science-parse or GROBID. They have been designed for that exact reason.

- I ended up using Grobid, which converts the PDF to a very detailed XML format. The format is not a word processing format though, but a format specifically for representing scientific documents. I don't know, if it would, for example, contain tags about bold or italicized text. The tool is working really well, but since you probably cannot use the output XML format directly, it will need some postprocessing, which would be relatively simple with XML parsing libraries.

A few years ago I evaluated a few open source tools. In the end focused on GROBID. As usual, it depends on the type of document whether it works well for your use-case. There is some focus on it being "fast" (if that is a concern).