Metaverse #
Metaverse is “An R ecosystem for meta-research”. It is a meta package which installs:
- synthsisr
- Import, assemble and de-duplicate bibliographic data
- litsearchr
- Quasi-automatic search strategy development for systematic reviews
- revtools
- Article screening for evidence synthesis using manual or visual methods
- metaDigitise
- High-throughput, reproducible extraction of data from figures
- robvis
- Publication quality risk-of-bias figures
synthsisr #
This package is designed mainly to simplify download and export of bibliographic information:
- Read and assemble bibliographic files
- synthesisr can read any BibTex or RIS formatted bibliographic data files. It detects whether files are more bib-like or ris-like and imports them accordingly
- Deduplicate bibliographic data
- Many journals are indexed in multiple databases, so searching across databases will retrieve duplicates. After import, synthesisr can detect duplicates and retain only unique bibliographic records using a variety of methods such as string distance or fuzzy matching records
- Write bibliographic files
- To facilitate exporting results to other platforms after assembly and deduplication, synthesisr can write bibliographic data to .ris or .bib files
litsearchr #
Litsearchr has a GUI which is in early development
Litsearchr identifies keywords by looking at an existing set of search results using algorithms such as Rapid Automatic Keyword Extraction (RAKE) (or a simple ngram search). The package can then group the keywords into concepts and then write a boolean search strategy. This can then be checked for precision and recall against a “Gold standard” of papers which should be returned by the search.
revtools #
Revtools is a package which allows the user to interact with their literature search using code as well as with a GUI. It includes:
- Locating duplicates
- Screening duplicates
- Screening of titles
- Screening of abstracts
- Creation of topic models to cluster and show similarity between papers
metaDigitise #
This package can extract data points from graphics, as well as computing statistics for data extracted from a graphic. It includes GUI elements to assist with the extraction.
robvis #
The robvis package takes the summary table from risk-of-bias assessments and produces plots formatted according to the assessment tool used
Resources for automation in systematic reviews #
A variety of point and click tools (with fairly restricted licences, on the whole)
Litstudy #
This is a Python package to help with literature reviews. It includes:
- Data import and merge
- Statistics (publication year, country of origin, number of authors etc.)
- Network analysis (co-citation network)
- Topic modelling (automatic topic discovery based on the words used in documents abstracts)
Appendix #
Cochrane guidelines on the use of automated tools in paper selection #
https://training.cochrane.org/handbook/current/chapter-04#section-4-6-6-2