grobid VS aleph

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.

If you're talking about tools for data, it really depends on what kind of data you're looking at and why you have it. For exploring datasets that you don't know what is contained inside (like data leaks) there's OCCRP's Aleph tool: https://github.com/alephdata/aleph

https://github.com/paperless-ngx/paperless-ngx https://github.com/alephdata/aleph

If you are doing investigative journalism, there is the OCCRP's Aleph for working with big amounts of data and connecting entities https://aleph.occrp.org/ . It's open source and self-hostable. Also for big messy dataset, the ICIJ's Datashare might be interesting.