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# cgraph
Scholarly citation graph related code; maintained by
[martin@archive.org](mailto:martin@archive.org); multiple subprojects to keep
all relevant code close.
* python: mostly [luigi](https://github.com/spotify/luigi) tasks (using
[shiv](https://github.com/linkedin/shiv) for single-file deployments)
* skate: various Go command line tools (packaged as deb)
Context: [fatcat](https://fatcat.wiki), "Mellon Grant" (20/21)
We use informal, internal versioning for the graph currently v2, next will be v3.
# Grant related tasks
3/4 phases of the grant contain citation graph related tasks.
* [x] Link PID or DOI to archived versions
> As of v2, we have linkage between fatcat release entities by doi, pmid, pmcid, arxiv.
* [ ] URLs in corpus linked to best possible timestamp (GWB)
> CDX API probably good for sampling; we'll need to tap into `/user/wmdata2/cdx-all-index/` - (note: try pyspark)
* [ ] Harvest all URLs in citation corpus (maybe do a sample first)
> A seed-list (from refs; not from the full-text) is done; need to prepare a crawl and lookups in GWB.
* [ ] Links between records w/o DOI (fuzzy matching)
> As of v2, we do have a fuzzy matching procedure (yielding about 5-10% of the total results).
* [ ] Publication of augmented citation graph, explore data mining, etc.
* [ ] Interlinkage with other source, monographs, commercial publications, etc.
> As of v3, we have a minimal linkage with wikipedia.
* [ ] Wikipedia (en) references metadata or archived record
> This is ongoing and should be part of v3.
* [ ] Metadata records for often cited non-scholarly web publications
* [ ] Collaborations: I4OC, wikicite
We attended an online workshop in 09/2020, organized in part by OCI members;
recording: [fatcat five minute
intro](https://archive.org/details/fatcat_workshop_open_citations_open_scholarly_metadata_2020)
# TODO
* [ ] create a first index, ES7 [schema PR](https://git.archive.org/webgroup/fatcat/-/merge_requests/99)
* [ ] build API, [spec notes](https://git.archive.org/webgroup/fatcat/-/blob/10eb30251f89806cb7a0f147f427c5ea7e5f9941/proposals/2021-01-29_citation_api.md)
# IA Use Cases
* [ ] discovery tool, e.g. "cited by ..." link
* [ ] things citing this page/book/...
* [ ] metadata discovery; e.g. most cited w/o entry in catalog
* [ ] Turn All References Blue (TARB)
# Additional notes
* [https://docs.google.com/document/d/1vg_q0lxp6CrGGFS4rR06_TbiROh9nj7UV5NFvueLRn0/edit](https://docs.google.com/document/d/1vg_q0lxp6CrGGFS4rR06_TbiROh9nj7UV5NFvueLRn0/edit)
# Current status
```
$ refcat.pyz BiblioRefV2
```
* schema: [https://git.archive.org/webgroup/fatcat/-/blob/10eb30251f89806cb7a0f147f427c5ea7e5f9941/proposals/2021-01-29_citation_api.md#schemas](https://git.archive.org/webgroup/fatcat/-/blob/10eb30251f89806cb7a0f147f427c5ea7e5f9941/proposals/2021-01-29_citation_api.md#schemas)
* matches via: doi, arxiv, pmid, pmcid, fuzzy title matches
* 785,569,011 edges (~103% of 12/2020 OCI/crossref release), ~39G compressed, ~288G uncompressed
# Rough Notes
* [python/notes/version_0.md](python/notes/version_0.md)
* [python/notes/version_1.md](python/notes/version_1.md)
* [python/notes/version_2.md](python/notes/version_2.md)
* [python/notes/version_3.md](python/notes/version_3.md)
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