Alexandria3k documentation¶
The alexandria3k package supplies a library and a command-line tool providing efficient relational query access to the following large scientific publication open data sets. Data are decompressed on the fly, thus allowing the package’s use even on storage-restricted laptops.
Crossref (157 GB compressed, 1 TB uncompressed). This contains publication metadata from about 134 million publications from all major international publishers with full citation data for 60 million of them.
PubMed (43 GB compressed, 327 GB uncompressed). This comprises more than 36 million citations for biomedical literature from MEDLINE, life science journals, and online books, with rich domain-specific metadata, such as MeSH indexing, funding, genetic, and chemical details.
ORCID summary data set (25 GB compressed, 435 GB uncompressed). This contains about 78 million author details records.
DataCite (22 GB compressed, 197 GB uncompressed). This comprises research outputs and resources, such as data, pre-prints, images, and samples, containing about 50 million work entries.
United States Patent Office issued patents (11 GB compressed, 115 GB uncompressed). This containins about 5.4 million records.
Further supported data sets include funder bodies, journal names, open access journals, and research organizations.
The alexandria3k package installation contains all elements required to run it. It does not require the installation, configuration, and maintenance of a third party relational or graph database. It can therefore be used out-of-the-box for performing reproducible publication research on the desktop.
Publication¶
Details about the rationale, design, implementation, and use of this software can be found in the following paper.
Diomidis Spinellis. Open reproducible scientometric research with Alexandria3k. PLoS ONE 18(11): e0294946. November 2023. doi: 10.1371/journal.pone.0294946
Package name derivation¶
The alexandria3k package is named after the Library of Alexandria, indicating how publication data can be processed in the third millenium AD.
Contents¶
- Installation
- Data downloading
- Use overview
- Command line examples
- Obtain list of available commands
- Show DOI and title of all publications
- Save DOI and title of 2021 publications in a CSV file suitable for Excel
- Show Crossref publications with more than 50 authors
- Count Crossref publications by year and type
- Obtain Patent Office granted patents by type
- Sampling
- Database of COVID research
- Publications graph
- Record selection from external database
- Populate the database with author records from ORCID
- Populate the database with journal names
- Populate the database with funder names
- Work with Scopus All Science Journal Classification Codes (ASJC)
- Populate the database with data regarding open access journals
- Populate the database with the names of research organizations
- Link author affiliations with research organization names
- Python API examples
- Create a Crossref object
- Iterate through the DOI and title of all publications
- Iterate through Crossref publications with more than 50 authors
- Create a dictionary of which 2021 publications were funded by each body
- Database of COVID research
- Reference graph
- Record selection from external database
- Populate the database from ORCID
- Populate the database with journal names
- Populate the database with funder names
- Populate the database with data regarding open access journals
- Work with Scopus All Science Journal Classification Codes (ASJC)
- Populate the database with the names of research organizations
- Link author affiliations with research organization names
- Application examples
- Schema diagrams
- Command line interface
- Python user API
- Python plugin API
- Python utility API
- Development processes
- Plugin development
- FAQ: Frequently asked questions